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# MLOps/AI Platform Engineer (6 months+ contract)

- **Company:** Anonymous Employer
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $176,800.0 - $228,800.0
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Applications Architecture, Application Integration Architecture, Software Applications, Audit Trail, User Authentication, Automation of Tests, Cloud Engineering, Configuration Management, Continuous Integration, Data Governance, Data Infrastructure, Data Retrieval, Identity and Access Management, Information Systems Security Architecture Professional, Python (Programming Language), Key Management, Knowledge-Based Systems, PostgreSQL, Load Testing, Machine Learning, Metadata, OAuth, OpenID, Role-Based Access Control, Search Technologies, Session Management, Microsoft SharePoint, Software Engineering, SQL Databases, Systems Integration, Enterprise Data Management, AWS Cdk, Data Logging, Chatbots, Data Ingestion, Spring Cloud, Flask (Web Framework), Delivery Pipeline, Multi-Agent Systems, Backend, Git, Cloudformation, Fastapi, SC Clearance, Containerization, AI Platforms, Kubernetes, Information Technology, Deployment Automation, Data Management, Machine Learning Operations, Cloudwatch, Api Gateway, Restful APIs, Terraform, Dynatrace, Devsecops, Docker, Databricks, Vulnerability Analysis
- **Published:** September 19, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9179318/mlopsai-platform-engineer-6-months-contract

## About the Role

* 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.

## Description

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.


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