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# AI Engineer (All Levels)

- **Company:** National Steel and Shipbuilding Com
- **Location:** San Diego, CA, United States
- **Experience:** Starter
- **Salary:** $90,300.0 - $159,900.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, DevOps, Key Management, Role-Based Access Control, Workflow Management Systems, Enterprise Data Management, Large Language Models, Prompt Engineering, Information Technology, Nintex, Key Vault, Microservices
- **Published:** September 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=276039ff22e0ea62

## About the Role

REQUIRED SKILLS AND QUALIFICATIONS Bachelor's degree in Computer Science, Information Technology, or related field, or equivalent education/experience. Minimum of 1-2 years' experience with LLMs, RAG, or AI solution development. Foundational understanding of Azure or other cloud platforms; exposure to Azure Gov is a plus. Interest or basic experience in prompt engineering, RAG architectures, and agentic AI workflows. Exposure to RBAC, secrets/key management (Key Vault), and data protection concepts. Strong organizational, verbal, and written communication skills. Ability to work in a fast-paced, evolving environment and respond with urgency to IT situations. This position may include other responsibilities and duties as assigned to support organizational security goals and initiatives, Work is generally performed in office conditions with good lighting. Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception, and the ability to adjust focus. The employee is regularly required to sit, use hands to fingers, handle or feel objects, or controls, and to talk and hear. Must be physically able to walk to all yard locations. May occasionally be exposed to working outdoors with moderate noise level.

## Description

The AI Engineer supports the design, build, and operation of production-grade AI solutions within Azure Government (GCCH) environments. The role focuses on implementing and testing LLM- and RAG-based solutions, assisting with agentic AI workflows, and learning how to securely connect AI agents to enterprise systems using MCP servers and related orchestration tools.

KEY RESPONSIBILITIES Assist in testing and evaluating LLMs and model variants (Azure OpenAI and other approved models) for performance and quality. Support RAG benchmarking (latency, relevance, accuracy, cost) and help optimize extraction engines, embeddings, and prompt strategies. Help build and configure MCP servers or similar integrations to securely connect AI agents to enterprise data and software. Assist in implementing agentic AI workflows (multi-step, tool-using agents) with platforms like N8N, Azure Foundry, and Copilot Studio. Contribute to design and implementation of simple, modular AI microservices and APIs for reuse across projects. Support BI and DevOps teams in adopting AI and ML capabilities and moving proofs of concept toward production. Help implement RBAC, secrets/key management (Key Vault), and data protection for AI workloads. Assist with monitoring, incident response, and documentation for AI workloads in Azure Gov environments.