AI Engineer

The work

We are seeking to build a team to implement LLM models into our current analytic environment. This role ranges from Senior to Junior level Software Engineers to provide hands-on application engineering: agent orchestration, retrieval pipelines, tool integration, and the backend services that hold it together, deployed into a classified enterprise environment.

What you’ll do

Work varies with experience, but expect a mix of

Build agent components. Implement orchestration logic, tool integrations, and memory handling within agent-based applications with design support early on and increasing ownership as you go.

Work the retrieval pipeline. Document processing, embedding generation, retrieval configuration, prompt assembly. This is where most people learn what actually makes RAG work, and where you’ll spend real time.

Write the services. Python REST APIs supporting data retrieval, system integration, and agent workflows.

Handle the data. Process and transform structured and unstructured data for AI workflows; work with Postgres schemas and query performance.

Ship to production. Testing, deployment, and the enterprise realities of a classified environment.

Junior-level

We’re looking for a working software engineer who wants to move into AI. You should bring:

• Solid Python, with real production code behind you
• Experience building or consuming REST APIs
• Comfort with databases and SQL
• Some hands-on exposure to LLMs or a RAG prototype, an agent you wired up, a side project, a course. Curiosity you can point at, not a credential
• Bachelor’s in computer science or a related field (additional experience considered in lieu)

You do not need prior professional AI work. We’ll teach the domain.

Mid-level

Same foundation, plus you’ve shipped something AI-enabled

• Hands-on work building LLM-integrated applications, RAG workflows, or retrieval-based systems
• Working familiarity with agent concepts for at least one AI framework
• Understanding of the fundamentals: how transformers behave, why context windows matter, where retrieval breaks down
• Enough production experience to have opinions about reliability and maintainability

Senior-level

You will design and lead the team to provide end to end orchestration within the platform.

• 8+ years of software engineering experience overall with recent hands-on work building AI/ML applications
• Bachelor’s in computer science or a related field
• Strong Python and fluency with common data and AI libraries
• Demonstrated experience with LLM-integrated applications, RAG workflows, or similar retrieval-based systems
• Working knowledge of agent-based programming
• Solid grounding in the fundamentals: transformers, LLM behavior, data processing, model integration patterns
• Experience designing or integrating REST APIs
• Production engineering habits: testing, reliability, deployment

Must have

• Active TS Clearance

Nice to have

• FastAPI or Flask
• Vector databases, embedding models, semantic search
• Docker and containerized development
• AWS or comparable cloud environments
• MCP or similar agent-to-tool protocols
• Anything you’ve built on your own time and can walk us through

Pay: $120,000.00 - $210,000.00 per year

Benefits

• 401(k)
• 401(k) matching
• Dental insurance
• Employee assistance program
• Employee discount
• Flexible schedule
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Parental leave
• Professional development assistance
• Referral program
• Tuition reimbursement
• Vision insurance

Security clearance

• Top Secret (Required)

Work Location: In person