SME AI/ML Engineer

Agile Defense•Fort Meade, MD
•$200,000 - $215,000•Onsite

About The Position

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.

Requirements

  • Master's degree and 8+ years of relevant experience
  • 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
  • Active TS/SCI w/ polygraph

Responsibilities

  • 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.
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