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Job Description: Conversational AI Expert

Location: Onsite - Noida

Department: AI/ML

Experience: 2+ Years

About the Role

We are looking for a Conversational AI Expert to design, develop, and deploy AI/ML models for our multimodal EdTech platform. The ideal candidate will work closely with the AI/ML Lead to build intelligent systems that understand student context, personalize learning journeys, and enhance engagement through text, voice, and visual AI capabilities.

In this role, you will work on conversational AI systems, recommendation engines, OCR for handwritten notes, predictive analytics, and adaptive learning algorithms that respond to student behavior and emotional states.

Key Responsibilities

• Develop and deploy conversational AI models, including dialogue systems, context managers, and NLP pipelines.
• Build personalization and recommendation engines to enhance student learning experiences.
• Implement OCR models for handwritten educational content.
• Work with AI/ML Lead to design multimodal AI features (text, voice, and visual).
• Develop predictive analytics models for student performance and engagement.
• Integrate vector databases and semantic search for efficient knowledge retrieval.
• Optimize ML model performance through A/B testing, monitoring, and tuning.
• Collaborate with product and engineering teams to deploy real-time inference solutions.

Required Skills

• 2+ years of hands-on AI/ML engineering experience.
• Strong expertise in NLP, conversational AI, chatbots, and dialogue management.
• Experience with recommendation systems and personalization algorithms.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, etc.).
• Experience with vector databases (FAISS, Pinecone, Milvus) and semantic search.
• Familiarity with LLMs, fine-tuning, prompt engineering, and model integration.
• Strong understanding of A/B testing and AI model optimization.

Nice to Have

• Experience integrating speech-to-text (STT) and text-to-speech (TTS) systems.
• Exposure to multimodal AI (text + voice + visual).
• Knowledge of predictive analytics and student behavior modeling.
• Prior experience in EdTech or consumer-facing AI/ML applications.
• Experience with real-time inference optimization and model deployment.

Why Join Us?

• Work on cutting-edge multimodal AI projects in the EdTech domain.
• Opportunity to shape new-age learning through personalized AI systems.
• Collaborative culture with strong focus on innovation and experimentation.

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Title - AI Engineer

Type - Contract

Location - Hybrid, Chennai

Roles and Responsibilities:

• Architect and implement end-to-end full-stack solutions for Agentic AI applications that integrate real-time and historical data to facilitate autonomous decision-making.
• Design, develop, and deploy intelligent agents using frameworks such as LangChain and LangGraph, leveraging large language models (LLMs) for document authoring, semantic search, and recommendation systems.
• Build scalable, secure, and compliant chatbot interfaces that serve enterprise needs.
• Develop and maintain robust data pipelines using Python, Snowflake SQL, and various AWS-native services to ensure seamless data flow and processing.
• Integrate graph databases like Neo4j and vector databases to enable semantic search capabilities and contextual reasoning.
• Deploy scalable AI services on cloud platforms including AWS (Bedrock, Lambda, ECS), Azure AI, and GCP.
• Collaborate with cross-functional teams across business, data science, and engineering to translate complex workflows into intelligent automation solutions.
• Ensure all AI systems comply with regulatory and operational standards, documenting architecture, deployment processes, and governance practices.
• Lead the development and deployment of AI agents for document retrieval and generation in large-scale enterprise environments, including Copilot Studio agent creation.
• Promote AI governance and ethics by adhering to principles of fairness, transparency, privacy, and responsible AI model integration, especially within regulated industries (e.g., FDA Part 11, GMP).
• Mentor junior engineers, lead technical workshops, and drive proof-of-concept projects to foster innovation and knowledge sharing.
• Communicate effectively with stakeholders to align AI solutions with business goals and operational requirements.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 5+ years of professional software engineering experience with at least 3 years focused on AI/ML and large language model-based systems.
• Advanced proficiency in Python programming.
• Hands-on experience with LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex or similar AI frameworks.
• Deep understanding of LLM architectures, prompt engineering, retrieval-augmented generation (RAG), and semantic search methodologies.
• Experience working with embedding-based search systems and graph technologies such as Neo4j and GraphRAG.
• Proficiency in cloud AI platforms including Azure AI, AWS (Bedrock, Lambda, ECS), and Google Cloud Platform (GCP).
• Strong experience with containerization and orchestration tools including Docker, Kubernetes, and infrastructure as code using Terraform.
• Expertise in building scalable APIs using frameworks such as FastAPI and Flask, and integrating them with enterprise systems.
• Familiarity with CI/CD pipelines and observability tools to ensure reliable deployment and monitoring of AI services.
• Knowledge of AI ethics, governance, and compliance frameworks applicable to regulated industries.
• Demonstrated leadership skills with experience mentoring teams and managing cross-functional collaboration.

Tools and Technologies:

• Programming Languages & Frameworks: Python, FastAPI, Flask
• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex
• Databases: Neo4j, Vector Databases
• Cloud Platforms: AWS (Bedrock, Lambda, ECS), Azure AI, GCP
• Containerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform
• Data Processing & Pipelines: Snowflake SQL, AWS-native services
• DevOps & CI/CD: CI/CD pipelines, observability tools
• Other: Knowledge of AI governance, ethical AI

Position: Permanent

Role: AI Developer

Experience: 5 Years

Location: Chennai / Bangalore / Pune

Shift Timing: General Shift

About the Role

We are seeking an experienced AI Engineer with proven expertise in developing AI Agents and implementing Agentic AI capabilities. The ideal candidate will also have deep knowledge in designing and managing Knowledge Graphs (KG) using GraphDB, enabling intelligent reasoning, contextual awareness, and semantic data enrichment in enterprise-grade AI systems.

Responsibilities

• Design and develop autonomous AI agents using agentic design patterns (e.g., reflection, reasoning, tool-use, collaboration).
• Implement multi-agent systems capable of task delegation, planning, and decision-making.
• Build and maintain Knowledge Graphs using GraphDB to support semantic search, contextual reasoning, and data enrichment.
• Integrate AI agents with external tools, APIs, and databases to enable dynamic workflows.
• Collaborate with data scientists, domain SMEs, and architects to define ontology models, entity relationships, and graph schemas.
• Optimize agent performance through feedback loops, RLHF, and context-aware protocols (e.g., MCP).
• Ensure scalability, security, and compliance of AI systems across cloud and hybrid environments.
• Document tech

About Techmagnate

Techmagnate is a leading digital performance marketing agency delivering measurable business growth through SEO, Paid Media, Content, and Analytics. As we integrate AI into every layer of marketing and operations, we are seeking a visionary Head – AI & Automation to lead our next wave of digital transformation.

Role Overview

The Head – AI & Automation will define and drive Techmagnate’s AI strategy across business functions—from marketing operations, reporting and analytics to sales operations and client delivery. This leader will identify, implement, and optimize AI solutions that enhance performance, productivity, and innovation.

Key Responsibilities

• AI Strategy & Roadmap: Define and implement Techmagnate’s AI vision and long-term roadmap across departments (SEO, PPC, Content, HR, Sales).
• Innovation Leadership: Identify emerging AI and LLM tools relevant to marketing and integrate them into campaign operations.
• Automation Initiatives: Lead the design and deployment of automated workflows across CRM, lead nurturing, content production, and performance tracking.
• Internal Efficiency: Implement AI systems that streamline recruitment, reporting, and client servicing.
• Client Solutions: Collaborate with business heads to create AI-based services, pr

Total Yrs. of Experience: 9+ yrs

Relevant Yrs. of experience: 7+ yrs

Detailed JD:

• AI/ML Engineer
• Someone with experience in fundamental models, cloud, LAMA, etc.
• This individual should have the aptitude to do POCs, evaluate various LLMs that meet the needs

Domain: Cards and payments

Work Location: Pune

Mode of Interview: Virtual

Mode of work: Hybrid

Role: AI/ML & Generative AI Architect / Engineering Leader

Experience : 15 + Years

Location : Pune

Mandatory-Should have a stable track record

Suitable candidate shall be notified the same day

About the Role

We’re looking for a Technology Leader in AI/ML and Generative AI with strong experience in architecting, designing, and delivering enterprise-grade AI platforms . The ideal candidate will combine deep hands-on expertise in LLMs, RAG, Agentic AI, and Azure AI Services with enterprise architecture and engineering leadership skills.

You will drive the AI-first transformation journey for large enterprises, build AI-powered digital expert systems , and lead teams to deliver scalable, secure, and business-aligned AI solutions.

Key Responsibilities

• Architect and implement AI/ML and Generative AI platforms for large-scale enterprise adoption.
• Design and productionize AI-powered systems for Banking use cases such as onboarding, payments, and cash management.
• Develop RAG pipelines, Agentic AI workflows , and LLMOps frameworks using LangChain, LangGraph, and Hugging Face.
• Integrate solutions with Core Banking, ERP, H2H, and API platforms ensuring scalability, security, and compliance.
• Lead and mentor high-performing engineering

Role: AI/ML & Generative AI Architect / Engineering Leader

Experience : 15 + Years

Location : Pune

Mandatory-Should have a stable track record

Suitable candidate shall be notified the same day

About the Role

We’re looking for a Technology Leader in AI/ML and Generative AI with strong experience in architecting, designing, and delivering enterprise-grade AI platforms . The ideal candidate will combine deep hands-on expertise in LLMs, RAG, Agentic AI, and Azure AI Services with enterprise architecture and engineering leadership skills.

You will drive the AI-first transformation journey for large enterprises, build AI-powered digital expert systems , and lead teams to deliver scalable, secure, and business-aligned AI solutions.

Key Responsibilities

• Architect and implement AI/ML and Generative AI platforms for large-scale enterprise adoption.
• Design and productionize AI-powered systems for Banking use cases such as onboarding, payments, and cash management.
• Develop RAG pipelines, Agentic AI workflows , and LLMOps frameworks using LangChain, LangGraph, and Hugging Face.
• Integrate solutions with Core Banking, ERP, H2H, and API platforms ensuring scalability, security, and compliance.
• Lead and mentor high-performing engineering

Role: AI/ML & Generative AI Architect / Engineering Leader

Experience : 15 + Years

Location : Pune

Mandatory-Should have a stable track record

Suitable candidate shall be notified the same day

About the Role

We’re looking for a Technology Leader in AI/ML and Generative AI with strong experience in architecting, designing, and delivering enterprise-grade AI platforms . The ideal candidate will combine deep hands-on expertise in LLMs, RAG, Agentic AI, and Azure AI Services with enterprise architecture and engineering leadership skills.

You will drive the AI-first transformation journey for large enterprises, build AI-powered digital expert systems , and lead teams to deliver scalable, secure, and business-aligned AI solutions.

Key Responsibilities

• Architect and implement AI/ML and Generative AI platforms for large-scale enterprise adoption.
• Design and productionize AI-powered systems for Banking use cases such as onboarding, payments, and cash management.
• Develop RAG pipelines, Agentic AI workflows , and LLMOps frameworks using LangChain, LangGraph, and Hugging Face.
• Integrate solutions with Core Banking, ERP, H2H, and API platforms ensuring scalability, security, and compliance.
• Lead and mentor high-performing engineering

Role: Artificial Intelligence Engineer

Location: Linnk Innovation Hub, Cochin

Company: Linnk Group – A fast-growing tech company building AI-powered SaaS platforms (CRM, ERP, automation, and more).

Key Objectives

• Lead AI initiatives to embed intelligence across Linnk’s SaaS products.
• Develop NLP, chatbots, computer vision, predictive models, and automation tools.
• Collaborate cross-functionally to build scalable, cloud-native AI solutions.
• Ensure ethical, responsible AI deployment aligned with business outcomes.

Responsibilities

• Define and drive Linnk’s AI vision and roadmap.
• Build and deploy AI models (NLP, recommendation systems, predictive analytics).
• Integrate AI into SaaS platforms using microservices and APIs.
• Conduct research, document best practices, and mentor junior engineers.
• Stay ahead of AI trends to keep Linnk competitive.

Required Skills

• 2+ years experience in applied AI/ML.
• Strong in Python, TensorFlow/PyTorch, NLP tools (spaCy, Hugging Face).
• Experience with chatbots, recommendation engines, predictive models.
• Familiar with APIs, data pipelines, and distributed systems.
• Understanding of AI ethics and data privacy.

Preferred

• Degree in CS, AI/ML, or related.

Company Description

Our client is a next-generation cloud services company that transforms businesses through the power of digital innovation. Its team of certified cloud experts brings hands-on experience in building, migrating, and managing complex cloud environments with precision. The company delivers tailored solutions that drive real business impact and measurable outcomes. Fueled by passion, collaboration, and creativity, they are shaping the future in Cloud, Data, and IoT , helping clients grow, evolve, and lead in the digital era.

Role Description

This is a full-time role for an Artificial Intelligence Engineer. The position is based in Chennai. The AI Engineer will be responsible for designing, developing, and optimizing AI models and algorithms. The role will also include collaborating with cross-functional teams, refining software development processes, and integrating AI systems into business applications.

Qualifications

• 3+ years of experience in C# and .NET Core
• Must have at least 6 months of recent experience in developing AI Agents using Semantic Kernel
• Excellent knowledge in C#
• Good knowledge in Generative AI and LLM (Azure OpenAI preferred)
• Good knowledge in Semantic Kernel and the different Agent orchestration patterns available
• Good knowledge in Agentic AI concepts
• High level awareness of various AI

About Eximiets:

Eximietas Design is a technology services and solutions company headquartered in San Jose, CA India. Specialising in Cloud Computing, Cybersecurity, VLSI, Embedded Software, and Artificial Intelligence, Eximietas is dedicated to empowering businesses with cutting-edge innovations, ensuring their digital future is secure, efficient, and poised for growth. We foster a vibrant, collaborative work culture that thrives on innovation and inclusivity. Rooted in the spirit of Silicon Valley's tech dynamism, our global teams are united by a passion for excellence in technology and engineering.

Job Title: AI Engineer (Autogen, Azure AI and OpenAI)

Location: Bangalore

Work Mode - Work from Office ( 5 days )

Notice Period - Earliest joiner / Currently serving / Less than 30 days NP

Job Description:

Seeking an AI Automation Engineer skilled in GenAI, Autogen Framework, Azure AI ( All mandatory) Services, and RAG systems to build AI-driven automation solutions.

Key Responsibilities:

 Develop AI solutions using AgenticAI, Autogen, Prompt engineering and Azure AI.

 Implement multi-agent AI systems and RAG (Retrieval-Augmented Generation) systems.

 Optimise AI workflows with Azure Functions, Logic Apps, and APIs.

 Deploy and fine-tune LLMs (GPT, Claude, Gemini).

 Ensu

Job Title :: Python Artificial Engineer

Location :: India (Remote)

Minimum relevant experience :: 6

Top Skills:

• Python Coding
• Agentic AI
• LangGraph
• FastAPI

Job Description:

• We are seeking a highly motivated AI Engineer with hands-on experience in developing and deploying agentic AI architectures. The ideal candidate is proficient in Python, has worked with frameworks like LangGraph, and understands the practical implementation of AI/ML solutions. Experience in machine learning or deep learning is a plus but not required.

Key Responsibilities:

• Design, build, and deploy agentic AI systems, leveraging modern frameworks.
• Develop and maintain scalable AI workflows using LangGraph and related tools.
• Collaborate with cross-functional teams to integrate AI agents into real-world applications.
• Write clean, efficient, and testable Python code.
• (Optional) Apply data science techniques to train and fine-tune ML or deep learning models.

Required Skills:

• Strong proficiency in Python and related libraries.
• Experience with agentic AI architectures and autonomous AI agents.
• Hands-on experience with LangGraph or similar orchestration frameworks.
• Understanding of AI lifecycle: prompt engineering, agent workfl

Seeking an AI Engineer to design, implement, and enhance AI-driven features using large language models and modern AI frameworks. This role focuses on integrating pre-trained models with frameworks such as LangChain, LangGraph, and LangSmith, as well as performing model fine-tuning and customization.

Responsibilities:

• Develop AI features with Node.js, TypeScript, and Express.
• Build LLM applications using LangChain, LangGraph, or LangSmith.
• Optimize prompts and manage conversational context.
• Translate requirements into AI capabilities.
• Ensure robust testing and monitoring of AI features.
• Stay updated on LLM/AI framework advancements.

Must Have:

• Proficiency in Node.js and TypeScript
• Experience with LangChain, LangGraph and LangSmith
• Experience with Express
• Prompt engineering / optimization
• Strong problem-solving skills

Qualifications & Experience:

• Bachelor’s or Master’s in CS or related field.
• 3+ years as an AI Engineer.

Preferred:

• Experience with model fine-tuning
• Familiarity with Python
• Experience with OpenAI APIs

We are looking for AI/GenAI Developer with very strong knowledge in Python, AI/GenAI . Should have experience in building RAG pipelines with various LLM's . Having knowledge in Microsoft Copilot studio is an advantage.

Position: AI/GenAI Developer

Location: Remote/Offshore

Type: Fulltime (40 hours per week)

Duration: 12+ Months

Need an Immediate Joiner!

Requirements:

5+ years of experience in AI/ML architecture, with at least 3 years focused on enterprise-level projects

Deep understanding of GenAI technologies, including LLMs, diffusion models, and transformer architectures

Extensive experience with enterprise integration patterns, APIs, and middleware solutions

Proficiency in cloud platforms (AWS, Azure, or GCP) and their AI/ML offerings

Strong programming skills in Python.

Experience with ML frameworks such as TensorFlow, PyTorch, or Hugging Face

Familiarity with DevOps and MLOps practices for AI model deployment and management

Excellent communication skills and ability to translate complex technical concepts to non-technical stakeholders

Knowledge of data privacy regulations and AI ethics

Experience with graph databases and knowledge graphs for AI applications

StitchFin is an innovative startup revolutionizing the healthcare space by building cutting-edge AI solutions. We are seeking an enthusiastic AI engineer/Data Sciences leader to head the development of cutting-edge voice AI systems and intelligent agents. In this role, you will design, develop, and deploy advanced AI models and systems that deliver exceptional user experiences through conversational interfaces.

Responsibilities

AI Development and Deployment

• Develop and maintain AI-driven, real-time speech-to-speech conversational agents and Agentic systems
• Design and implement end-to-end AI pipelines and fine tune models
• Optimize AI systems for performance, scalability, and reliability
• Collaborate on defining and tracking success metrics for AI features

Technical Requirements

• 5+ years of hands-on software engineering experience with Python or similar languages
• Experience building and scaling distributed systems in cloud environments
• Proficiency in API design
• Proficiency with generative AI frameworks and tools
• Hands on experience with large language models, prompt engineering.
• Demonstrated ability to write clean, maintainable, and well-tested code
• Experience with CI/CD pipelines, cloud platforms like AWS and deployment automation
• Knowledge of monitoring, observability, and production debugging tools
• F

Experience: 3-5 YOE in AI/ML

Location: Bangalore

AI Engineer

Skills we’re seeking:

✨ Azure AI Studio, Prompt Flow, and OpenAI on Azure

✨ Azure AI Foundry, Copilot Studio (Agent Creation & Lifecycle Management)

✨ Power Platform – Power Automate & Power Apps

✨ GitHub Copilot & Responsible AI integration

✨ MLOps pipeline deployment and Azure Cloud expertise

✨ Knowledge of Microsoft 365 (M365) platform

If this sounds like you or someone you know, share your updated profile at goteti.sudheshna@movate.com

We are looking for a Sr AI/ML Engineer / Developer with product development experience.

1. Knowledge and experience with common ML and Data Engineering APIs – e.g., clustering, pdf extraction etc.

2. Knowledge and experience with the APIs of all the major LLMs – e.g., OpenAI, Perplexity, DeepSeek, Anthropic etc

3. Knowledge and Experience with Langchain and Langgraph APIs

4. Knowledge and Experience with Langchain Templates – e.g, ChatPromptTemplate and RAG Template, etc.

5. Experience using vector databases and Graph Databases – e.g., Neo4j, Allegrograph

6. Setting up Python-based API Endpoints

7. Setting up and running Data Engineering pipelines.