Job Requirements
Remote
Secret Polygraph not specified
Career Level not specified
$180,000 - $210,000
Job Description
Senior MLOps / AI Platform Engineer
Program: Federal Defense Program
Location: Remote
Clearance Required: Active Secret Clearance
Employment Type: Full-Time Contract
Background Investigation / Drug Screening: Required
Hourly W2 rate: $85-110/hr W2
PLEASE NOTE THIS CONTRACT STARTS AT 6 MONTHS WITH HIGH LIKLIHOOD OF EXTENSION
Overview
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.
Required Qualifications
• 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.
Key Responsibilities
• 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.
• Experience working with:
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.
Preferred Qualifications
• 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.
Program: Federal Defense Program
Location: Remote
Clearance Required: Active Secret Clearance
Employment Type: Full-Time Contract
Background Investigation / Drug Screening: Required
Hourly W2 rate: $85-110/hr W2
PLEASE NOTE THIS CONTRACT STARTS AT 6 MONTHS WITH HIGH LIKLIHOOD OF EXTENSION
Overview
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.
Required Qualifications
• 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.
Key Responsibilities
• 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.
• Experience working with:
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.
Preferred Qualifications
• 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.
group id: kforcecx