AI Engineer
Backend Developer
Ai Agent Systems
APIs
Artificial Intelligence
Cloud Operations
Data Analysis
Data Analytics
Data Engineer
Data Integration
Data Pipeline
Data Processing
Database
Databases
Generative AI
Information Technology (IT)
Large Language Models
Machine Learning
Programming
Programming Language
Programming Languages
Rag Architectures
Software Development
SQL
Web Framework
Job Description
Embedded Alliance is hiring an AI Engineer for an onsite role in Herndon, VA (classified enterprise environment). You’ll work on implementing LLM models in support of analytics workflows, bringing together agent orchestration, retrieval (RAG), and production-grade engineering practices.
This position offers a USD 120,000 - 210,000 yearly salary range and supports ongoing growth through professional development assistance and tuition reimbursement.
What you’ll do
- Implement orchestration logic for agent-based applications, including tool integrations and memory handling
- Build end-to-end retrieval capabilities: document processing, embedding generation, retrieval configuration, and prompt assembly
- Develop Python REST APIs that support data retrieval, system integration, and agent workflows
- Process and transform structured and unstructured data for AI workflows, working with Postgres schemas and query performance
- Handle testing, deployment, and the operational realities of a classified environment
- Design and lead the team to deliver end-to-end orchestration within the platform
Required qualifications
- Active TS Clearance
- 8+ years of software engineering experience overall, with recent hands-on work building AI/ML applications
- Solid Python with real production code experience
- Experience building or consuming REST APIs
- Comfort with databases and SQL
- Hands-on exposure to LLMs or a RAG prototype (example: wired an agent, side project, course)
- Curiosity you can point to, not a credential
- Bachelor’s in computer science or a related field (additional experience may be considered in lieu)
- Understanding of fundamentals such as transformers, context windows, and where retrieval breaks down
- Production engineering habits focused on testing, reliability, and deployment
- Working familiarity with agent concepts for at least one AI framework
- Demonstrated experience with LLM-integrated applications, RAG workflows, or similar retrieval-based systems
Nice to have
- FastAPI or Flask
- Vector databases, embedding models, and 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 that you can walk through
Benefits
- 401(k) and 401(k) matching
- Health insurance, Dental insurance, Vision insurance
- Health savings account and Flexible spending account
- Life insurance
- Paid time off and Parental leave
- Employee assistance program and Employee discount
- Flexible schedule
- Professional development assistance, Tuition reimbursement
- Referral program
Technologies you may work with
- Python, REST APIs
- Postgres, SQL
- LLMs, RAG, FastAPI, Flask
- Vector databases, embedding models, semantic search
- Docker, AWS
- MCP
Security clearance: Top Secret (Required)
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