Applied AI / LLM Solutions Engineer

Applied AI / LLM Solutions Engineer

Requires Active TS/SCI with Full Scope Polygraph

Location: Annapolis Junction, MD (hybrid; 2 days/week onsite, up to 3 days/week remote)

Employment Type: Direct Hire, Full-Time

Clearance Requirement: Candidates must currently hold an active Top Secret clearance with SCI with Full Scope (CI) Polygraph. This requirement cannot be sponsored or waived.

The Opportunity:

We're looking for an AI Engineer to help build and maintain mission-driven AI capabilities, working alongside systems and software engineers to design, prototype, and weave AI functionality into existing platforms. This isn't a model-training role it's about applying today's leading large language models to real operational workflows. You'll be building agentic systems coordinated networks of AI agents and prompts that take over tasks currently done by hand, tighten up authoring and reporting pipelines, and sharpen the overall effectiveness of intelligence operations.

What You'll Be Doing:

• Building Agentic Systems: Own the full lifecycle of AI-driven solutions, from early concept through production deployment architecting multi-agent pipelines where coordinated agents and prompts jointly generate outputs that feed reporting and dissemination. This spans prototyping, writing clean production code, and keeping deployed capabilities running smoothly.
• Connecting Foundation Models to Mission Systems: Wire existing foundation models into current software environments through APIs and orchestration layers picking the right model and method for each use case rather than building models in-house.
• Prompt Design & Task Automation: Craft, test, and iterate on prompts and agent instructions so manual tasks run reliably on autopilot, breaking down complicated mission processes into steps an agent pipeline can carry out.
• Output Validation & Quality Control: Build out testing and evaluation frameworks to confirm AI-generated outputs are accurate, consistent, and handle edge cases appropriately before anything reaches analysts or final reports.
• Cross-Team Technical Liaison: Act as a bridge between system engineers, developers, and subject-matter experts clearly explaining recommended AI approaches and walking both technical and non-technical stakeholders through the tradeoffs of different implementation paths.
• Staying Ahead of the Curve: Keep pace with the fast-moving world of LLMs and agentic AI new models, orchestration tools, frameworks and continually look for practical ways to bring emerging capabilities into the system.

Must-Have Experience:

• Solid Python development background, capable of writing clean, maintainable, production-grade code
• Practical experience building on top of existing LLMs (commercial or self-hosted, accessed via API)
• Background designing multi-step or multi-agent AI workflows prompt chaining, tool use, agent orchestration (frameworks like LangChain, LlamaIndex, or custom-built pipelines)
• Strong prompt-crafting skills, with experience evaluating and validating LLM output quality
• Experience weaving AI capabilities into existing software systems (RESTful APIs, microservices architecture)
• Hands-on experience with AWS cloud infrastructure

Nice-to-Have:

• Experience with retrieval-augmented generation (RAG) pipelines and vector database integration
• Familiarity with tooling for LLM observability and performance evaluation
• Experience exploring and analyzing structured/unstructured datasets to prep inputs for AI pipelines
• Exposure to MLOps/LLMOps practices for scaled deployment and monitoring of AI systems
• Working knowledge of government reporting and dissemination policy frameworks