Generative AI Data Engineer

Build and deploy GenAI capabilities in a classified enterprise environment with a team focused on practical delivery. Embedded Alliance supports your growth with professional development assistance, tuition reimbursement, and a benefits package designed for long-term well-being, including flexible scheduling and generous time off.

This onsite role in Herndon, VA implements LLM models into an analytic environment. You will work on production-oriented agent orchestration, retrieval pipelines (RAG), tool integration, and Python-based REST APIs that connect data retrieval to agent workflows.

Responsibilities

• Implement orchestration logic, tool integrations, and memory handling within agent-based applications, with design support early and increasing ownership over time.
• Handle document processing, embedding generation, retrieval configuration, and prompt assembly.
• Develop Python REST APIs to support data retrieval, system integration, and agent workflows.
• Process and transform structured and unstructured data for AI workflows, working with Postgres schemas and improving query performance.
• Own testing and deployment with attention to the realities of a classified environment.
• Design and lead team efforts to deliver end-to-end orchestration within the platform.

Requirements

• Active TS Clearance.

Level expectations

• Junior-level: Solid Python with production code; experience building or consuming REST APIs; comfort with databases and SQL; hands-on exposure to LLMs or a RAG prototype (via project or learning); Bachelor’s in computer science or related field (additional experience considered in lieu).
• Mid-level: 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 transformer fundamentals and context window behavior; enough production experience to form opinions on reliability and maintainability.
• Senior-level: 8+ years of software engineering with recent hands-on AI/ML application work; Bachelor’s in computer science or 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; experience integrating REST APIs; production engineering habits including testing, reliability, and deployment.

Technologies

Python, REST APIs, Postgres, SQL, LLMs, RAG, Elasticsearch, Docker, MCP

Nice to have

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

Benefits

• 401(k) and 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

Compensation: USD 120,000 - 210,000 per year

Experience: 8+ years

Education: Bachelor’s in computer science or a related field