Operationalize the program's AI governance framework: model capability tiering, use-case approval workflow, rules of engagement, and audit/logging requirements
Support security accreditation activities, including AO engagement, RMF documentation inputs, and responsible AI evidence
Build and optimize data pipelines feeding AI-driven features; integrate with existing program systems and workflows
Establish code quality, testing, and documentation standards for the AI engineering function; mentor mid-level developers as the team grows
Brief technical approach and results to program leadership and government customers
Required Qualifications
Active TS/SCI with polygraph to start
Security+CE or other IAT Level II or higher certification required to start
Bachelors degree or equivalent experience.
8+ years of professional software development experience (or 6+ with a relevant advanced degree), including 3+ years building or integrating ML/AI capabilities
Expert-level Python; working proficiency in at least one additional language (JavaScript/TypeScript, Java, or similar)
Demonstrated experience deploying or serving LLMs or ML models in disconnected, on-premises, or government cloud environments (Azure Government, AWS GovCloud, or equivalent)
Practical experience with model inference, embeddings, vector search, and prompt engineering in production systems
Experience with containerization (Docker/Kubernetes or equivalent) and CI/CD in restricted environments
Strong understanding of data security, classification handling, and responsible AI practices
Proven ability to work directly with government customers and translate mission requirements into technical solutions
Preferred Qualifications
Experience supporting RMF accreditation or AO engagement for AI/ML systems
Familiarity with open-weight model deployment (Llama, Mistral, or similar) and model quantization/optimization for constrained hardware
Experience with ML frameworks (PyTorch preferred)
Prior work on IC or DoD programs; NRO experience a significant plus
