Generative AI Data Engineer

Embedded Alliance, Inc.; Herndon (VA); On-site; USD 120,000 - 210,000; Full time

Benefits offered by this job

401(k) matching

Dental insurance

Employee assistance program

Flexible schedule

Flexible spending account

Health insurance

Health savings account

Life insurance

Paid time off

Parental leave

Professional development assistance

Tuition reimbursement

Vision insurance

Referral program

Job summary

Embedded Alliance, Inc. in Herndon, VA, is seeking a seasoned engineer to build and deploy GenAI capabilities in a classified environment.

You’ll implement agent orchestration, retrieval pipelines (RAG), tool integration, and Python-based REST APIs tying data retrieval to agent workflows. The role requires an active TS clearance and offers onsite work with a strong emphasis on testing, reliability, and production-grade deployment of AI applications.

Qualifications

• Active TS clearance required.
• Bachelor’s in computer science or related field.
• 8+ years of software engineering with AI/ML experience for senior level.

Responsibilities

• Implement orchestration logic and tool integrations for agent-based applications.
• Handle document processing, embedding generation, retrieval configuration, and prompt assembly.
• Develop Python REST APIs to support data retrieval and agent workflows.
• Work with Postgres schemas and optimize query performance.
• Own testing and deployment in a classified environment.
• Lead end-to-end orchestration within the platform.

Skills

Python

REST APIs

Postgres

SQL

LLMs

RAG

Elasticsearch

Docker

Agent concepts

Testing

Education

Bachelor’s in Computer Science

Tools

Docker

Elasticsearch

MCP

Job description

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