AI/ML Automation EngineerLocation: Government Facility (Hybrid/Onsite) Security Clearance: Active Secret Clearance Required (TS/SCI Preferred) Customer: U.S. Department of Homeland Security (DHS) Employment Type: Full-TimeArgo Cyber Systems is a Service-Disabled Veteran-Owned Small Business (SDVOSB) delivering advanced cybersecurity engineering, artificial intelligence, cloud security, digital forensics, threat intelligence, and cyber modernization services to Federal agencies and critical infrastructure organizations.We are seeking an experienced AI/ML Automation Engineer to architect and implement intelligent automation capabilities that enhance cyber operations, malware analysis, digital forensics, and mission decision-making. This role combines machine learning engineering, generative AI, cloud-native development, and workflow automation to build scalable AI solutions supporting national cybersecurity missions.The AI/ML Automation Engineer serves as the senior technical lead responsible for designing, developing, deploying, and optimizing AI-driven capabilities across cybersecurity operations.You will collaborate with cyber analysts, data scientists, software engineers, cloud architects, and mission stakeholders to implement advanced machine learning models, Large Language Model (LLM) integrations, Retrieval-Augmented Generation (RAG) solutions, autonomous agent workflows, and intelligent automation supporting operational cyber missions.This position offers the opportunity to shape next-generation AI capabilities used in support of incident response, malware analysis, threat intelligence, digital forensics, and cybersecurity modernization.Primary ResponsibilitiesDesign, develop, and deploy enterprise AI and machine learning solutions supporting cybersecurity operations.Develop intelligent automation using LLMs, foundation models, and autonomous AI agents.Build Retrieval-Augmented Generation (RAG) pipelines for secure knowledge retrieval.Design prompt engineering strategies and optimize AI model performance.Develop feature engineering, data preparation, and ML training pipelines.Support model evaluation, tuning, validation, and continuous improvement.Design end-to-end automation workflows for cyber operations.Automate malware collection, detonation, classification, and analysis.Build AI-driven orchestration supporting incident response and digital forensics.Develop APIs enabling secure data exchange between cyber platforms.Automate repetitive analytical processes to improve operational efficiency.Design cloud-native AI solutions using AWS services.Develop AI integrations utilizing Amazon Bedrock and foundation models.Implement scalable ML pipelines using Databricks and cloud data platforms.Deploy containerized AI workloads using Docker and Kubernetes.Build CI/CD pipelines supporting rapid AI model deployment.Design and maintain scalable data ingestion pipelines.Build data transformation, normalization, and enrichment workflows.Develop streaming data integrations supporting AI workloads.Optimize data quality, governance, and operational performance.Support structured, semi-structured, and unstructured data processing.Develop AI-enabled malware analysis capabilities.Support AI-driven threat intelligence enrichment.Build detection engineering automation.Develop machine learning capabilities supporting digital forensics.Assist cyber analysts by integrating AI decision-support capabilities into operational workflows.Provide technical leadership for AI modernization initiatives.Mentor engineers on AI engineering best practices.Collaborate with cybersecurity SMEs and software development teams.Develop architecture documentation, design artifacts, and technical standards.Present AI capabilities to executive leadership and government stakeholders.Required QualificationsU.S. CitizenshipActive Secret Security ClearanceAbility to obtain DHS Entry on Duty (EOD) SuitabilityBachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Computer Engineering, or related STEM fieldFive (5) or more years of professional experience developing AI, ML, automation, or data engineering solutionsStrong Python development experienceExperience with Databricks AI PlatformExperience implementing machine learning pipelinesExperience integrating Large Language Models (LLMs)Experience with Amazon Bedrock and AWS AI servicesExperience building REST APIs and cloud-native applicationsExperience with Git, CI/CD pipelines, and software development best practicesStrong analytical, problem-solving, and communication skillsPreferred QualificationsActive TS/SCI ClearanceExperience supporting DHS, CISA, NSA, FBI, DoD, or Intelligence Community programsExperience implementing Generative AI solutionsExperience developing autonomous AI agentsExperience building RAG architecturesExperience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar AI orchestration frameworksExperience with vector databases (Pinecone, FAISS, ChromaDB, OpenSearch Vector Engine)Experience supporting malware analysis, digital forensics, or threat intelligenceExperience implementing MLOps pipelinesExperience deploying AI into production cloud environmentsDesired Technical SkillsArtificial IntelligenceLarge Language Models (LLMs)Generative AIRetrieval-Augmented Generation (RAG)Prompt EngineeringAI AgentsAgentic AIModel Fine-TuningReinforcement LearningNatural Language Processing (NLP)Embedding ModelsMachine LearningTensorFlowPyTorchScikit-learnXGBoostML PipelinesFeature EngineeringModel EvaluationModel DeploymentCloudAWSAmazon BedrockSageMakerLambdaECSEKSS3IAMCloudWatchDatabricksData EngineeringSparkKafkaKinesisAirflowPrefectSQLNoSQLData LakesETL/ELTVector DatabasesSoftware EngineeringPythonFastAPIREST APIsDockerKubernetesGitGitHub ActionsJenkinsTerraformCybersecurityMalware AnalysisThreat IntelligenceIncident ResponseDigital ForensicsMITRE ATT&CKDetection EngineeringSIEM IntegrationSecurity AutomationDesired CertificationsAWS Certified Machine Learning – SpecialtyAWS Certified AI PractitionerAWS Solutions Architect – Professional
