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? If so, then apply today and be part of a team that supports the United States Cyber Command (USCC). Our team is standing up USCYBERCOM's 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 of the USCC. What You'll Be Doing: Research, design, develop, and test operating systems-level software, compilers, and network distribution software for medical, industrial, military, communications, aerospace, business, scientific, and general computing applications. Set operational specifications and formulate and analyze software requirements. May design embedded systems software. Apply principles and techniques of computer science, engineering, and mathematical analysis. • 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. Requirements • Bachelor's degree from an accredited college or university in Computer Science, Data Science, or a related discipline and 10+ years of experience; 4 additional years of experience may be considered in lieu of degree • Active TS/SCI clearance w/Poly • 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 Preference to Candidates that Have: • Master's degree and 8+ years of relevant experience • Experience supporting USCYBERCOM, NSA, DoD cyber operations, or related 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 • Experience supporting USCYBERCOM, NSA, or DoD AI/cyber mission environments TS/SCI with polygraph is required.

Requirements

Must-haves

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.
Bachelor's degree from an accredited college or university in Computer Science, Data Science, or a related discipline and 10+ years of experience; 4 additional years of experience may be considered in lieu of degree
Active TS/SCI clearance w/Poly
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
Master's degree and 8+ years of relevant experience
Experience supporting USCYBERCOM, NSA, DoD cyber operations, or related 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
Experience supporting USCYBERCOM, NSA, or DoD AI/cyber mission environments
TS/SCI with polygraph is required.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

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