AI Engineer

Chenega Corporation•Atlanta, GA

3d•Hybrid

About The Position

Chenega Services & Federal Solutions, LLC, a Chenega Professional Services company, is seeking an AI Engineer to support the Centers for Disease Control and Prevention (CDC). The position is contingent on contract award, and details may change based on the final award. The role defines and delivers mission-critical AI-enabled web applications that address complex client challenges, applying generative AI to create retrieval-based knowledge assistants, chatbots, and agentic workflows with data processing, orchestration, and multi-agent components behind intuitive user interfaces. The engineer collaborates with enterprise and solutions architects, product owners, AI engineers, data engineers, and DevSecOps teams to deliver secure, scalable, maintainable production solutions. The position develops and enhances production generative AI applications using Azure AI Foundry, Azure OpenAI, and Foundry Agent Service. It involves building RAG systems, knowledge assistants, chatbots, and agentic workflows; integrating APIs, enterprise data sources, databases, cloud services, and MCP-based tools; and developing cloud-native services and user interfaces using Python, web frameworks, containers, and Azure services. The engineer also tests, evaluates, and monitors applications to improve quality, reliability, latency, and cost. The candidate must currently be located in Atlanta, Georgia, or Washington, DC, and be able to work onsite when needed. The posted work arrangement is hybrid, with onsite work in Atlanta, Georgia. The role requires a bachelor's degree in computer science, engineering, or a related field, at least five years of relevant hands-on technical experience, and at least one year building generative or agentic AI solutions. A Public Trust or suitability determination must be obtainable and maintainable as required by the client or contract. The estimated salary range is $105,000 to $120,000 per year, with final salary based on skill set, qualifications, and approved funding.

Requirements

Currently located in Atlanta, GA, or Washington, DC, and able to work onsite when needed.
At least 5 years of hands-on technical experience in software engineering, web application development, data engineering, data science, machine learning, or a related technical discipline.
At least 1 year of hands-on experience building generative AI or agentic AI solutions, including LLM APIs, prompt engineering, tool/function calling, structured outputs, 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.
Experience with 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.

Nice To Haves

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 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 and collaborate with software, AI/ML, data, cloud, and DevSecOps engineers.
Ability to clearly communicate technical problems, implementation decisions, and trade-offs to technical and non-technical stakeholders.

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 using 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.
Collaborate with AI engineers, software engineers, architects, and DevSecOps teams to deliver maintainable production applications.

Benefits

Paid time off, including vacation accrual of 5.67 hours per pay period (136 hours annually).
11 paid holidays.
Medical insurance.
Dental insurance.
Vision insurance.
Prescription coverage.
Employee Assistance Program.
Short- and long-term disability insurance.
Life and AD&D insurance.
Flexible Spending Account.
Health Savings Account.
Health Reimbursement Account.
Dependent Care Spending Account.
Commuter benefits.
401(k) / 401(a) retirement plans.
Hospital indemnity coverage.
Critical illness coverage.
Accident insurance.
Pet insurance.
Legal insurance.
ID theft protection.
California residents receive an additional 24 hours of sick leave per year.