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/Data 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

Elasticsearch optimization
Docker and containerized development
MCP or similar agent-to-tool protocols

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

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