AI Engineer - Multiple Openings and Multiple Seniority Levels

Summary

Position contingent on contract award - d etails below are subject to change based on final award.

Come join a company that strives for Extraordinary People and Exceptional Performance ! Chenega Services & Federal Solutions, LLC , a Chenega Professional Services’ company, is looking for multiple AI Engineers to join our team supporting the Centers for Disease Control and Prevention (CDC).

Mutliple openings!

Mid-level AI Engineers - 2 - salary range: $82,000-92,000

Senior-level AI Engineer - 1 - salary range: $108,000-118,000

Our company offers employees the opportunity to join a team where there is a robust employee benefits program, management engagement, quality leadership, an atmosphere of teamwork, recognition for performance, and promotion opportunities. We actively strive to channel our highly engaged employee’s knowledge, critical thinking, innovative solutions for our clients.

Responsibilities

Mid-level responsibilities:

Build, enhance, and support production generative AI applications and web-based AI solutions.

Develop Python backend services and AI integrations using Azure OpenAI, Azure AI Foundry, and related Azure services.

Implement RAG pipelines, including document processing, chunking, embeddings, search, context preparation, and source citations.

Implement agent workflows using tool/function calling, structured outputs, conversation context, error handling, execution limits, and human review where needed.

Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools.

Test and evaluate retrieval relevance, answer correctness and grounding, reliability, latency, and cost.

Add logging, tracing, and metrics to monitor model calls, retrieval steps, tool execution, errors, and token usage.

Troubleshoot application issues, fix defects, and support deployments and production monitoring.

Participate in code reviews, document implementation decisions, and collaborate with engineering and DevSecOps teams.

Senior-level responsibilities:

Build, enhance, and support production generative AI applications and web-based AI solutions.

Develop AI applications using Azure AI Foundry, Azure OpenAI, and Foundry Agent Service.

Build and improve advanced retrieval-augmented generation (RAG) systems, knowledge assistants, chatbots, and multi-turn conversational experiences.

Implement agent and multi-agent workflows using tool/function calling, structured outputs, controlled execution, 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 backend services using Python, web frameworks, containers, and Azure services.

Test, evaluate, and monitor AI applications to improve retrieval relevance, answer correctness and grounding, reliability, latency, and cost.

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

Qualifications

Mid-level AI Engineer requirements:

3+ years of technical experience, including developing and supporting production software applications

1+ year of hands-on generative AI development, including RAG-based assistants or chatbots

Experience with Python backend development, including asynchronous APIs, using FastAPI, Pydantic, or comparable tools

Experience with Git, code reviews, automated testing, CI/CD, and Agile team delivery

Experience with Azure, including Azure OpenAI, Azure AI Search, and integration with databases and external services

Ability to demonstrate agent workflow experience with tool calling, structured outputs, and context management using PydanticAI, Microsoft Agent Framework, LangGraph, Foundry Agent Service, or similar tools

Ability to conduct LLM evaluation and troubleshooting using test datasets, logs, and traces to assess quality, latency, and cost

Possession of hands-on RAG experience with document processing, chunking, embeddings, vector or hybrid search, and citations

Bachelor’s degree in computer science, engineering, or a related field

Senior-level AI Engineer requirements:

5+ years of hands-on technical experience in software engineering, web application development, data engineering, data science, machine learning, or a related technical discipline, including building, deploying, and supporting production applications

2+ years of hands-on, client-facing experience building generative AI solutions, including practical delivery of RAG-based knowledge assistants

Strong Python application development experience, including asynchronous programming, APIs, backend services, and frameworks such as FastAPI and Pydantic or comparable tools

Hands-on experience with advanced RAG techniques, including document chunking, embeddings, hybrid keyword/vector search, semantic ranking, query rewriting, retrieval filters, multi-turn context, and source citations

Hands-on experience implementing agentic and multi-agent workflows, including intent-based routing, tool/function calling, structured outputs, context management, and execution limits and error handling

Experience with at least one agent framework, such as PydanticAI, Microsoft Agent Framework, LangGraph, or a comparable framework, and with Azure AI Foundry Agent Service

Hands-on experience with Microsoft Azure, including Azure OpenAI and Azure AI Search, and deploying or integrating applications with cloud-hosted services

Experience with REST APIs, JSON-based interfaces, databases, and external service integrations

Experience evaluating and troubleshooting LLM applications using test datasets, tracing, and monitoring to assess answer correctness, retrieval quality, latency, and cost

Experience using modern software-development practices, including Git, pull requests, code reviews, automated testing, CI/CD, issue tracking, and Agile/Scrum delivery practices

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

Final salary determination based on skill-set, qualifications, and approved funding.

Many of our jobs come with great benefits – Some offerings are dependent upon the role, work schedule, or location, and may include the following:

Paid Time Off

PTO / Vacation – 5.67 hours accrued per pay period / 136 hours accrued annually

Paid Holidays - 11

California residents receive an additional 24 hours of sick leave a year

Health & Wellness

Medical

Dental

Vision

Prescription

Employee Assistance Program

Short- & Long-Term Disability

Life and AD&D Insurance

Spending Account

Flexible Spending Account

Health Savings Account

Health Reimbursement Account

Dependent Care Spending Account

Commuter Benefits

Retirement

401k / 401a

Voluntary Benefits

Hospital Indemnity

Critical Illness

Accident Insurance

Pet Insurance

Legal Insurance

ID Theft Protection

Teleworking Permitted?

Yes Teleworking Details

Remote - US Estimated Salary/Wage

USD $82,000.00/Yr. Up to USD $118,000.00/Yr.

Mid-level responsibilities:

Build, enhance, and support production generative AI applications and web-based AI solutions.

Develop Python backend services and AI integrations using Azure OpenAI, Azure AI Foundry, and related Azure services.

Implement RAG pipelines, including document processing, chunking, embeddings, search, context preparation, and source citations.

Implement agent workflows using tool/function calling, structured outputs, conversation context, error handling, execution limits, and human review where needed.

Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools.

Test and evaluate retrieval relevance, answer correctness and grounding, reliability, latency, and cost.

Add logging, tracing, and metrics to monitor model calls, retrieval steps, tool execution, errors, and token usage.

Troubleshoot application issues, fix defects, and support deployments and production monitoring.

Participate in code reviews, document implementation decisions, and collaborate with engineering and DevSecOps teams.

Senior-level responsibilities:

Build, enhance, and support production generative AI applications and web-based AI solutions.

Develop AI applications using Azure AI Foundry, Azure OpenAI, and Foundry Agent Service.

Build and improve advanced retrieval-augmented generation (RAG) systems, knowledge assistants, chatbots, and multi-turn conversational experiences.

Implement agent and multi-agent workflows using tool/function calling, structured outputs, controlled execution, 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 backend services using Python, web frameworks, containers, and Azure services.

Test, evaluate, and monitor AI applications to improve retrieval relevance, answer correctness and grounding, reliability, latency, and cost.

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

Mid-level AI Engineer requirements:

3+ years of technical experience, including developing and supporting production software applications

1+ year of hands-on generative AI development, including RAG-based assistants or chatbots

Experience with Python backend development, including asynchronous APIs, using FastAPI, Pydantic, or comparable tools

Experience with Git, code reviews, automated testing, CI/CD, and Agile team delivery

Experience with Azure, including Azure OpenAI, Azure AI Search, and integration with databases and external services

Ability to demonstrate agent workflow experience with tool calling, structured outputs, and context management using PydanticAI, Microsoft Agent Framework, LangGraph, Foundry Agent Service, or similar tools

Ability to conduct LLM evaluation and troubleshooting using test datasets, logs, and traces to assess quality, latency, and cost

Possession of hands-on RAG experience with document processing, chunking, embeddings, vector or hybrid search, and citations

Bachelor’s degree in computer science, engineering, or a related field

Senior-level AI Engineer requirements:

5+ years of hands-on technical experience in software engineering, web application development, data engineering, data science, machine learning, or a related technical discipline, including building, deploying, and supporting production applications

2+ years of hands-on, client-facing experience building generative AI solutions, including practical delivery of RAG-based knowledge assistants

Strong Python application development experience, including asynchronous programming, APIs, backend services, and frameworks such as FastAPI and Pydantic or comparable tools

Hands-on experience with advanced RAG techniques, including document chunking, embeddings, hybrid keyword/vector search, semantic ranking, query rewriting, retrieval filters, multi-turn context, and source citations

Hands-on experience implementing agentic and multi-agent workflows, including intent-based routing, tool/function calling, structured outputs, context management, and execution limits and error handling

Experience with at least one agent framework, such as PydanticAI, Microsoft Agent Framework, LangGraph, or a comparable framework, and with Azure AI Foundry Agent Service

Hands-on experience with Microsoft Azure, including Azure OpenAI and Azure AI Search, and deploying or integrating applications with cloud-hosted services

Experience with REST APIs, JSON-based interfaces, databases, and external service integrations

Experience evaluating and troubleshooting LLM applications using test datasets, tracing, and monitoring to assess answer correctness, retrieval quality, latency, and cost

Experience using modern software-development practices, including Git, pull requests, code reviews, automated testing, CI/CD, issue tracking, and Agile/Scrum delivery practices

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

Final salary determination based on skill-set, qualifications, and approved funding.

Many of our jobs come with great benefits – Some offerings are dependent upon the role, work schedule, or location, and may include the following:

Paid Time Off

PTO / Vacation – 5.67 hours accrued per pay period / 136 hours accrued annually

Paid Holidays - 11

California residents receive an additional 24 hours of sick leave a year

Health & Wellness

Medical

Dental

Vision

Prescription

Employee Assistance Program

Short- & Long-Term Disability

Life and AD&D Insurance

Spending Account

Flexible Spending Account

Health Savings Account

Health Reimbursement Account

Dependent Care Spending Account

Commuter Benefits

Retirement

401k / 401a

Voluntary Benefits

Hospital Indemnity

Critical Illness

Accident Insurance

Pet Insurance

Legal Insurance

ID Theft Protection