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TCS Hiring for Cloud Engineer- AWS Cloud Services

Experience Range: - 08 To 12 Years (Mandatory)

(Note: Candidates below 8 years of IT experience shall not be considered)

JOB LOCATION: Bengaluru, Chennai, Hyderabad, Pune, Kochi, Bhubaneswar

JOB DESCRIPTION

• Proficient and experienced in some of the services like - AWS Infra and Network services, Control Tower, AWS Organizations, Service Control Policies, VPC, Cloud Factory, Machine Image management
• Expert in some of the services like EC2, Lambda, S3, Cloud Formation, AWS Step Functions, AWS SSM, AWS IAM, AWS Security, AWS Backup, AWS ACM, KMS
• Experience in monitoring Tools like Datadog, PagerDuty, Cloud Watch, Cloud Trail, SIEM integration
• Scripting experience - Terraform, Ansible, Python, AWS CLI
• Service management, Release and Change management processes and tools
• Tooling experience; Jenkins CI/CD , Puppet, Packer
• Windows (2019/2022/2025) and/or Redhat Linux (7/8/9/10) to an admin level in an enterprise context. Preferably within a Cloud platform.

Minimum Qualification

15 years of Full Time Education

Interested candidates kindly share your updated resume to immediately with the details below (Mandatory)

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Any gaps between your education or career (If yes pls specify the duration):

Will you be able to join within 30/45 days? (Yes/NO)

Job Title: Senior AI Cloud Engineer (AWS & Generative AI)

Location: Pune, India

Role Type: Contract

Role Overview

We are seeking a highly technical Cloud Engineer to build and optimize our Generative AI infrastructure. This role focuses on deploying AWS Bedrock agents, automating workflows with Python , and creating robust observability and billing pipelines for LLM usage. You will be responsible for ensuring that our AI services are not only functional but also cost-effective and highly monitored through advanced logging and alerting.

Key Responsibilities

• AI Agent Orchestration: Design and deploy specialized agents using AWS Agents for Amazon Bedrock to automate complex multi-step business processes.
• Observability & Alerting: Build end-to-end "Data Log" pipelines. Identify and implement the correct AWS services for alerting (e.g., CloudWatch, SNS, or Lambda) based on log anomalies.
• Integration & Middleware: Manage and analyze Mulesoft logs to ensure seamless connectivity between legacy systems and modern AI services.
• Financial Operations (FinOps): Monitor billing metrics for LLM usage and AWS

About the Role

We are looking for a Senior Cloud Engineer with 5–8 years of experience to build and scale cloud-native ML infrastructure and deployment platforms across Azure, Databricks, Kubernetes, and MLOps environments.

The ideal candidate should have strong hands-on experience in cloud application development, Kubernetes-based deployments, automation, and platform engineering — not just operational DevOps support. We are specifically looking for candidates with deep expertise in cloud-native architecture, infrastructure automation, and scalable ML deployment systems.

Work from Office – Minimum 4 Days/Week

⚡ Immediate Joiners or Candidates with Notice Period up to 15 Days Preferred

Tech Stack

Azure | Databricks | AKS | ARO | Terraform | MLflow | CI/CD

Key Responsibilities

• Build and maintain CI/CD/CT pipelines for ML and cloud-native applications
• Develop scalable deployment workflows for MLflow models, Databricks jobs, and microservices on AKS/ARO
• Build cloud-native infrastructure and deployment automation using Terraform and GitOps practices
• Design and manage Kubernetes-based application deployment environments
• Develop automation scripts and platform tooling using Python, Bash, or PowerShell
• Optimize Databricks, AKS clusters, networking, and model serving environments
• Implemen