MLOps/AI Platform Engineer (6 months+ contract)

We are seeking a Senior MLOps / AI Platform Engineer to support a large-scale federal modernization initiative focused on delivering advanced AI and machine learning capabilities in a secure cloud environment. This role will be responsible for building, integrating, deploying, and operating AI-powered chatbot and orchestration platforms, while supporting enterprise data sources, vector databases, and cloud-hosted services. The ideal candidate will bring deep expertise in AWS cloud technologies, MLOps, AI application development, platform engineering, and Databricks integrations. This position requires a hands-on engineer who can design scalable solutions, implement secure architectures, and support production AI workloads in highly regulated environments., * Design, build, deploy, and operate AI-enabled applications and platform services within AWS environments.

• Develop and maintain chatbot and AI orchestration services that integrate with enterprise data sources and cloud-native technologies.
• Build scalable APIs, backend services, and AI-enabled applications using Python.
• Implement production-grade MLOps pipelines supporting model deployment, monitoring, and lifecycle management.
• Collaborate with cloud engineers, data architects, and application teams to deliver secure and scalable AI solutions.
• Develop and maintain containerized applications supporting enterprise AI and machine learning workloads.
• Troubleshoot and resolve infrastructure, networking, application, authentication, and performance issues.
• Implement security controls, governance standards, and monitoring capabilities for AI applications operating in regulated environments.
• Create observability solutions including monitoring, logging, tracing, alerting, and performance analytics.
• Drive automation initiatives across CI/CD processes, deployment pipelines, testing frameworks, and platform operations.

Required Technical Skills AWS & Cloud Engineering

• Hands-on experience building and deploying AI/ML applications utilizing AWS services, including: o Amazon Bedrock o SageMaker o API Gateway o ECS o EKS o ECR o S3 o IAM o Secrets Manager o KMS o CloudWatch

• Experience deploying and supporting cloud-native applications in scalable production environments. AI/ML Application Development

• Experience developing AI-powered applications, chatbot solutions, or orchestration platforms.
• Strong Python development skills.

• Experience utilizing frameworks such as: o FastAPI o Flask o LangChain o LangGraph o Similar AI application frameworks

• Experience implementing retrieval-augmented generation (RAG), structured-data retrieval, and hybrid question-answering solutions. Databricks

• Strong experience integrating applications with Databricks services and APIs.

• Active Secret Clearance.
• Approximately 15+ years of overall IT experience.
• 9+ years of experience in MLOps, cloud engineering, platform engineering, DevSecOps, or AI application development.
• Experience supporting Department of Defense or other federal government environments.
• Strong experience with AWS GovCloud environments.

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience., o Databricks REST APIs o SQL Warehouses o OAuth Authentication o Unity Catalog o SQL Statement Execution APIs

• Experience supporting enterprise data platforms and governed data environments. Containerization & Platform Engineering

• Experience containerizing Python applications and APIs using Docker.

• Experience deploying workloads to: o ECS o EKS o Kubernetes

• Experience designing scalable, resilient, and highly available application architectures. Vector Databases & Knowledge Platforms

• Experience integrating AI applications with vector search and knowledge retrieval solutions including: o Amazon OpenSearch o Bedrock Knowledge Bases o PostgreSQL/pgvector o Databricks Vector Search

• Experience developing document ingestion pipelines supporting: o SharePoint o S3 o File repositories o Enterprise knowledge systems

• Experience with metadata enrichment, embeddings generation, synchronization, and content lifecycle management. Security & Identity

• Experience implementing: o OAuth/OIDC authentication o Service principal authentication o Secrets management o Server-side session management o Least privilege IAM architectures

• Experience designing secure AI environments with strong auditability and governance controls. DevSecOps & CI/CD

• Experience creating and supporting CI/CD pipelines for containerized applications.

• Experience with: o Automated testing o Vulnerability scanning o Image promotion o Deployment automation o Rollback strategies o Configuration management

• Familiarity with Git-based development workflows and modern DevSecOps practices. Observability & Performance Engineering

• Experience implementing production monitoring and observability frameworks.

• Experience with: o Application logging o Distributed tracing o Metrics collection o API latency monitoring o Model utilization monitoring o Alerting and operational dashboards

• Experience load testing and scaling AI-enabled applications to support production workloads., * Experience supporting AWS GovCloud, DoD IL4/IL5, CUI, or similarly regulated environments.
• Experience deploying or integrating applications within large-scale federal data platforms.
• Experience with Databricks Genie, Databricks Vector Search, AI Search, and advanced data governance capabilities.

• Experience with: o Terraform o CloudFormation o AWS CDK o Helm o Kubernetes

• Experience supporting reusable chatbot frameworks, APIs, or enterprise web integrations across multiple applications.

Why Join?

• Long-term federal modernization effort with strong program funding.
• Fully remote work environment.
• Opportunity to work with cutting-edge AI, cloud, and machine learning technologies.
• High-impact role supporting advanced analytics and mission-focused decision-making capabilities.
• Collaborative engineering environment utilizing modern DevSecOps and cloud-native development practices.