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# AI Engineer - Senior

- **Company:** Elite
- **Location:** Washington, DC, United States (Remote available)
- **Experience:** Expert
- **Salary:** $176,800.0 - $208,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Web Interfaces, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Integration Architecture, JIRA, User Authentication, Automation of Tests, Microsoft Azure, Code Review, Databases, Continuous Integration, Information Engineering, Web Development, JSON, Python (Programming Language), Machine Learning, Open Source Technology, Scrum Methodology, Systems Development Life Cycle, OpenAI, Cloud Services, Software Engineering, Web Application Frameworks, Microsoft Agent Framework, Data Processing, Chatbots, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Backend, Agentic-AI, Build Management, Information Technology, Low Latency, Production Code, PydanticAI Framework, Evaluation of Large Language Models, Invoking Functions, Restful APIs, Model Context Protocol, Semantic Kernel, Data Pipelines, Devsecops, Serverless Computing, Human in the Loop, Docker, Container Apps
- **Published:** October 25, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=84226482957bdfa4

## About the Role

* 5+ years of hands-on experience in software engineering, web development, data engineering, data science, machine learning, or a related technical field
 * 1+ year of hands-on experience building generative or agentic AI solutions, such as LLM APIs, prompt engineering, tool/function calling, structured outputs, RAG, or agents
 * Strong Python development experience with APIs, backend services, data pipelines, and web frameworks
 * Experience with REST APIs, JSON interfaces, authentication, and third-party service integrations
 * Experience deploying or integrating applications on Microsoft Azure or AWS
 * Working knowledge of LLM fundamentals: tokens, context windows, system and user prompts, model parameters, embeddings, retrieval, and response evaluation
 * Experience with Git/GitHub, pull requests, code reviews, Jira, and Agile/Scrum delivery
 * Bachelor's degree in Computer Science, Engineering, or a related field
 * U.S. Citizen or Lawful Permanent Resident, able to obtain and maintain a Public Trust

Preferred Qualifications

 * Hands-on Azure AI Foundry, Azure OpenAI, or Foundry Agent Service experience
 * Model Context Protocol (MCP) integrations and multi-agent system development
 * Agent frameworks such as Microsoft Agent Framework, Semantic Kernel, LangGraph, or PydanticAI
 * LLM evaluation, tracing, monitoring, and observability
 * Docker plus Azure Container Apps, Azure App Service, or similar hosting
 * CI/CD and automated testing for AI applications
 * Experience in government, healthcare, or other regulated environments
 * Exposure to fine-tuning, hosting, or serving open-source LLMs
 * Knowledge of responsible AI, AI governance, and security and risk practices
 * Clear communicator who can explain technical trade-offs to technical and non-technical audiences

## Description

Elite Talent Hub is hiring an AI Engineer for a federal public health data modernization program. You will design and build production generative AI applications, including retrieval-based knowledge assistants, chatbots, and agentic workflows. The work puts data processing, orchestration, and multi-agent logic behind user-friendly web interfaces.

You will work alongside solutions architects, product owners, data engineers, and DevSecOps teams. Together you'll turn emerging AI capabilities into secure, scalable tools that change how public health professionals find information and make decisions. Candidates based in the Atlanta area are strongly preferred, and candidates in the Washington, DC area will also be considered.

What You'll Do

 * Build and improve production generative AI and web-based AI applications
 * Develop solutions with Azure AI Foundry, Azure OpenAI, and Foundry Agent Service
 * Design and implement RAG pipelines, knowledge assistants, chatbots, and agentic workflows
 * Build LLM and agent workflows that use tool calling, structured outputs, guardrails, and human-in-the-loop review
 * Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools
 * Develop secure, cloud-native services and user interfaces using Python, web frameworks, containers, and Azure services
 * Test, evaluate, and monitor AI applications for quality, reliability, latency, and cost
 * Collaborate with software, AI, and DevSecOps engineers to ship maintainable production code