AI Engineer

AI Engineer

Location: Atlanta, GA or the Washington, DC / Maryland / Virginia area Type: Direct Hire Compensation: $155,000.00 Work Model: Hybrid – onsite and remote

Responsibilities

• Build and enhance production generative AI applications and web-based AI solutions.
• Develop AI applications using Azure AI Foundry, Azure OpenAI, and Foundry Agent Service.
• Build retrieval-augmented generation (RAG) systems, knowledge assistants, chatbots, and agentic workflows.
• Implement agent and LLM workflows that use tools, structured outputs, guardrails, and human review where needed.
• Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools.
• Develop secure, cloud-native application services and user interfaces using Python, web frameworks, containers, and Azure services.
• Test, evaluate, and monitor AI applications to improve quality, reliability, latency, and cost.
• Work with AI engineers, software engineers, architects, and DevSecOps teams to deliver maintainable production applications.

Requirements

• 5+ years of hands-on technical experience in software engineering, web application development, data engineering, data science, machine learning, or related technical discipline
• 1+ years of hands-on experience building generative AI or agentic AI solutions, including LLM APIs, prompt engineering, tool/function calling, structured outputs, retrieval-augmented generation (RAG), agents, or similar techniques
• Experience developing applications with Python and working with APIs, backend services, data pipelines, and web application frameworks
• Experience with REST APIs, JSON-based interfaces, authentication mechanisms, and external service integrations
• Experience with at least one major cloud platform, such as Microsoft Azure or AWS, including deploying or integrating applications with cloud-hosted services
• Using modern software-development practices and collaboration tools, such as Git, GitHub, Jira, pull requests, code reviews, issue tracking, and Agile/Scrum delivery practices
• Knowledge of LLM application fundamentals, including tokens, context windows, system and user prompts, model parameters, structured outputs, embeddings, retrieval, and techniques for guiding and evaluating model responses
• Ability to obtain and maintain a Public Trust or suitability determination, as required by the client or contract
• Bachelor's degree in computer science, engineering, or a related field
• Must be a U.S. Citizen or Lawful Permanent Resident (Green Card Holder)

Desired Skills

• Experience with containerized or cloud-native application development, including Docker, Azure Container Apps, Azure App Service, or similar services
• Experience with Model Context Protocol (MCP) integrations and agent tool calling, including hands-on development of multi-agent systems
• Experience with implementing LLM evaluation, tracing, monitoring, and observability capabilities
• Experience with CI/CD, automated testing, and cloud-based development and deployment practices for AI applications
• Working in government, healthcare, or other regulated environments
• Exposure to fine-tuning, hosting, or serving open-source LLMs and working with model-serving frameworks
• Knowledge of AI governance, responsible AI principles, and related security and risk-management practices
• Knowledge of AI agent frameworks such as Microsoft Agent Framework, LangGraph, PydanticAI, or similar tools
• Ability to work effectively in a cross-functional engineering environment and collaborate with software, AI/ML, data, cloud, and DevSecOps engineers
• Clear communication of technical problems, implementation decisions, and trade-offs to both technical and non-technical stakeholders