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Agile Defense

Posted 25 days ago

Senior AI/ML EngineerAgile Defense · Fort Meade

Senior AI/ML Engineer

Fort MeadeOn-site

AI Summary

Designs and integrates LLM/agent orchestration workflows, RAG pipelines, and AI governance guardrails for a national mission AI platform, turning prototypes into production-grade capabilities.

About this role

About Agile Defense
At Agile Defense we know that action defines the outcome and new challenges require new solutions. That’s why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.
Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility—leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation’s vital interests.

Requisition #: 1920
Job Title: Senior AI/ML Engineer
Location: Fort Meade, MD | Onsite
Clearance Level: TS/SCI w/ Polygraph, Must Have Clearance to Start

Job Description

Ready for a challenge that puts you at the center of AI innovation for cyber operations? Are you an experienced AI/ML engineer who thrives in a fast-paced environment, enjoys turning research and prototypes into real mission capability, and wants to help shape how AI is built and delivered across a national mission?

Our team is standing up an AI Enterprise capability — the central hub that mission teams turn to when they want to move an AI solution from prototype to a secure, governed, enterprise-scale service. As a Senior AI/ML Engineer on this team, you will design and integrate the models, agents, and AI workflows that run on that platform, with significant, visible impact on the mission.

What You'll Be Doing:

  • Provide embedded operations support, capability integration, and rapid prototyping for AI/ML-enabled tools in support of our customer.
  • Design and integrate LLM/agent orchestration workflows using agentic frameworks such as LangGraph, Agno, and the NVIDIA NeMo Agent Toolkit.
  • Tune model gateway routing logic to select, evaluate, and optimize across multiple frontier and open-weight models for cost, performance, and mission fit.
  • Develop and integrate RAG pipelines, vector databases, and memory services to give agents access to mission knowledge and context.
  • Implement MCP (Model Context Protocol)-based tool-broker integrations so agents can safely and securely access enterprise tools and data.
  • Evaluate, benchmark, and tune models and agent behaviors; build automated evaluation pipelines to track quality, safety, and performance over time.
  • Partner with data scientists and mission analysts to translate research and prototypes into production-grade AI capabilities for the command.
  • Implement AI governance guardrails — content/safety filters, policy enforcement, and approval gates — for agentic workflows, and document model/agent architectures and evaluation results for reuse.
  • Research and evaluate emerging LLM, agent, and AI tooling to keep the command's AI capability current and adaptable.

    • Basic Qualifications

  • Bachelor’s degree from an accredited college or university in Computer Science, Data Science, or a related discipline and 8+ years of experience
  • Advanced proficiency in Python for AI/ML application development
  • Demonstrated experience building or integrating LLM/agent-based systems in production
  • Experience with retrieval-augmented generation (RAG), vector databases, and prompt/context engineering
  • Ability to manage competing priorities in fast-paced mission environments and identify/escalate operational risks early
  • Active TS/SCI clearance w/Poly

    • Preferred Skills

  • Experience supporting mission environments
  • Experience with frameworks such as LangGraph, Agno, or the NVIDIA NeMo Agent Toolkit
  • Experience with model inference/serving platforms (NVIDIA NIM, vLLM, Ollama, LiteLLM)
  • Experience with MCP (Model Context Protocol) or similar tool-broker/integration standards
  • Experience with AI evaluation frameworks, model benchmarking, and observability (logs/metrics/traces) for AI workloads

    • Skills

    AgnoAI Evaluation FrameworksContent Safety FiltersLangGraphLiteLLMMCP (Model Context Protocol)Model BenchmarkingNVIDIA NeMo Agent ToolkitNVIDIA NIMObservabilityOllamaPolicy EnforcementPrompt EngineeringPythonRAGVector DatabasesVLLM

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