Senior AI Engineer (FedD239)
Defenseunicorns · Springfield, VA
About this role
**Senior Platform Engineer — AI Engineering | Forward Deployed Engineering** Defense Unicorns is seeking a **Senior AI Agentic Engineer** to embed with a government team and its technology partners, building an emerging **AI-powered engineering ecosystem**. This role focuses on **designing, integrating, and operationalizing AI agents and agentic workflows** in a **secure enterprise environment**—turning AI capabilities into **reliable, mission-relevant production workflows**. --- ## Responsibilities - Design, build, and integrate **AI agents** and **multi-agent workflows** using modern LLM/agent technologies - Develop agent capabilities that interact with **enterprise applications, APIs, data sources, developer tools, and mission systems** - Integrate models, agents, tools, and enterprise data into **secure workflows** deployable in **controlled and classified environments** - Work with **LLMs, RAG, embeddings, vector databases, tool/function calling, structured outputs, MCP**, and related technologies - Enable agents to **securely discover, access, reason over, and act upon approved enterprise data/services** - Prototype and rapidly evaluate emerging models/frameworks to identify measurable mission/engineering value - Build evaluation/testing frameworks for **accuracy, reliability, safety, latency, cost, and task completion** - Implement **guardrails and policy controls** (tool access, data access, and human approval points) - Integrate agentic capabilities with **CI/CD and DevSecOps** for repeatable development, testing, deployment, and lifecycle management - Collaborate with platform engineers to operationalize AI workloads in **Kubernetes/OpenShift** environments - Work with commercial AI/technology partners to integrate capabilities into the broader ecosystem - Troubleshoot across **models, agent frameworks, APIs, data sources, networking, identity, and infrastructure** - Develop reusable patterns for **deployment, configuration, observability, evaluation, and lifecycle management** - Document architectures, integration patterns, agent specifications, evaluation results, and operational procedures - Identify recurring AI engineering challenges to standardize, automate, or productize - Stay current on evolving agentic AI technologies and assess applicability to secure government environments --- ## Minimum Experience & Qualifications - **Active Top Secret clearance** - Hands-on experience building applications/systems using **LLMs and generative AI** - Experience designing and implementing **AI agents / agentic workflows** - Strong programming experience in **Python and/or another modern language** - Experience integrating AI systems with **APIs, enterprise applications, databases, and external tools** - Experience with one or more **agent frameworks** or orchestration approaches - Working knowledge of **RAG, embeddings, vector databases, tool/function calling, structured outputs, and prompt engineering** - Experience developing software in **Git-based automated CI/CD** environments - Ability to rapidly prototype, test, troubleshoot, and iterate in ambiguous environments - Strong software engineering fundamentals (testing, version control, APIs, debugging, system design) - Ability to work effectively with platform engineers, government personnel, and multiple vendors --- ## Preferred Experience & Qualifications - Experience with **MCP (Model Context Protocol)** and tool-based agent architectures - Experience with **multi-age
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