AI Engineer

Support the CDC on a contingent contract award by building mission-critical AI-enabled web applications and secure generative AI solutions.

Responsibilities

• Build and enhance production generative AI applications and web-based AI solutions.
• Develop generative AI applications using Azure AI Foundry, Azure OpenAI, and Foundry Agent Service.
• Implement retrieval-augmented generation (RAG) systems, including knowledge assistants, chatbots, and agentic workflows.
• Create agent and LLM workflows that use tools, structured outputs, guardrails, and human review when required.
• 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.
• Collaborate with AI engineers, software engineers, architects, and DevSecOps teams to deliver maintainable production applications.

Requirements

• Currently located in Atlanta, GA or Washington, DC and able to work onsite when needed.
• 5+ years of hands-on technical experience in software engineering, web application development, data engineering, data science, machine learning, or related disciplines.
• 1+ years hands-on experience building generative AI or agentic AI solutions, including LLM APIs, prompt engineering, tool/function calling, structured outputs, and RAG/agents.
• 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 a major cloud platform such as Microsoft Azure or AWS, including deploying or integrating applications with cloud-hosted services.
• Experience with modern software-development practices and collaboration tools: Git, GitHub, Jira, pull requests, code reviews, issue tracking, and Agile/Scrum delivery.
• Knowledge of LLM application fundamentals, including tokens, context windows, system and user prompts, model parameters, structured outputs, embeddings, retrieval, and model response evaluation/guidance techniques.
• 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).

Technologies

• Azure AI Foundry, Azure OpenAI, Foundry Agent Service
• Python
• Web frameworks, containers, Azure services
• REST APIs, JSON
• Git, GitHub, Jira, Agile/Scrum
• MCP, LLM APIs, prompt engineering
• Tool/function calling, structured outputs, RAG, embeddings
• Docker, Azure Container Apps, Azure App Service
• Model Context Protocol (MCP), LangGraph, PydanticAI
• Microsoft Agent Framework, CI/CD

Benefits

• PTO / Vacation: 5.67 hours accrued per pay period / 136 hours accrued annually
• Paid Holidays: 11
• California residents: additional 24 hours of sick leave a year
• Medical, Dental, Vision
• Prescription
• Employee Assistance Program
• Short- & Long-Term Disability
• Life and AD&D Insurance
• Flexible Spending Account, Health Savings Account, Health Reimbursement Account
• Dependent Care Spending Account
• Commuter Benefits
• 401k / 401a
• Hospital Indemnity, Critical Illness, Accident Insurance
• Pet Insurance
• Legal Insurance, ID Theft Protection

Preferred Qualifications

• 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.
• Experience 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 across software, AI/ML, data, cloud, and DevSecOps.
• Ability to communicate technical problems, implementation decisions, and trade-offs to technical and non-technical stakeholders.

Location and Work Model

• Location: Atlanta, GA (hybrid)
• Teleworking permitted: FALSE
• Teleworking details: Hybrid - onsite work in Atlanta, GA

Compensation

• Estimated salary/wage: USD 105,000 - 120,000 per year