Poly

Parsons Corporation•Minneapolis, MN

1d•$148,300 - $266,900

About The Position

Parsons is seeking a Principal AI/ML Engineer to join their Federal Solutions team, supporting the United States Cyber Command (USCC). This role is central to establishing USCYBERCOM’s AI Enterprise capability, a hub for transitioning AI solutions from prototype to secure, enterprise-scale services. The engineer will design and integrate models, agents, and AI workflows with significant mission impact. The position requires an experienced AI/ML engineer who thrives in fast-paced environments, enjoys turning research into capability, and wants to influence AI development and delivery for a national mission.

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

Nice To Haves

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

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.