> Markdown version of [/jobs/ext/3376557-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/3376557-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Blu Omega - **Location:** Atlanta, GA, United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $155,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Integration Architecture, Application Services, JIRA, Authentication Protocols, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Engineering, Code Review, Collaborative Software, Databases, Continuous Integration, Corona (Software Development Kit), Information Engineering, Web Development, Github, Issue Tracking Systems, JSON, Python (Programming Language), Machine Learning, Open Source Technology, Scrum Methodology, Cloud Services, Software Engineering, Web Applications, Web Application Frameworks, Cloud Platform System, Chatbots, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Backend, Git, AI Platforms, Information Technology, Low Latency, Virtual Agents, Restful APIs, Data Pipelines, Devsecops, Docker - **Published:** September 30, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9181066/senior-ai-engineer ## About the Role * 5+ years of hands-on technical experience in software engineering, web application development, data engineering, data science, machine learning, or a related technical discipline. * 1+ years of hands-on experience developing generative AI or agentic AI solutions using LLM APIs, prompt engineering, tool/function calling, structured outputs, RAG, agents, or similar techniques. * Strong hands-on development experience with Python, APIs, backend services, data pipelines, and web application frameworks. * Experience working with REST APIs, JSON-based interfaces, authentication mechanisms, and external service integrations. * Experience with Microsoft Azure, AWS, or another major cloud platform, including deploying or integrating applications with cloud-hosted services. * Understanding of LLM application fundamentals, including tokens, context windows, system and user prompts, model parameters, embeddings, retrieval, structured outputs, and techniques for guiding and evaluating model responses. * Experience with modern software development and collaboration tools such as Git, GitHub, Jira, pull requests, code reviews, issue tracking, and Agile/Scrum practices. * Bachelor's degree in computer science, engineering, or a related field. * Ability to obtain and maintain a Public Trust or suitability determination, as required by the client or contract. * Must be a U.S. Citizen or Lawful Permanent Resident (Green Card Holder). Nice to Have * Hands-on experience with Azure AI Foundry, Azure OpenAI, Foundry Agent Service, or related Microsoft AI services. * Experience with Docker, Azure Container Apps, Azure App Service, or similar containerized and cloud-native application platforms. * Experience with Model Context Protocol (MCP), agent tool calling, and multi-agent application development. * Experience with AI agent frameworks such as Microsoft Agent Framework, LangGraph, PydanticAI, or similar technologies. * Experience implementing LLM evaluation, tracing, monitoring, observability, and quality-assurance capabilities. * Experience with CI/CD, automated testing, and cloud-based deployment practices for AI applications. * Exposure to fine-tuning, hosting, or serving open-source LLMs and associated model-serving frameworks. * Knowledge of AI governance, responsible AI, security, and AI risk-management practices. * Experience supporting government, healthcare, or other regulated environments. * Strong communication skills with the ability to explain technical problems, implementation decisions, and trade-offs to technical and non-technical stakeholders. * Eligible for Public Trust or equivalent clearance. ## Description Blu Omega is seeking an AI Engineer to design, develop, and deliver production-ready generative AI applications supporting mission-critical federal programs. In this role, you will build AI-enabled web applications, retrieval-based knowledge assistants, chatbots, and agentic workflows that help users access information, automate complex processes, and make better-informed decisions. You will work hands-on with large language models (LLMs), retrieval-augmented generation (RAG), AI agents, APIs, enterprise data sources, and cloud-native application services to turn emerging AI capabilities into practical, scalable solutions. You will collaborate with AI engineers, software engineers, enterprise and solution architects, data engineers, product owners, and DevSecOps teams to take AI solutions from concept through production. The ideal candidate combines strong Python and application development experience with hands-on generative AI expertise and an understanding of how to build, evaluate, secure, and operate LLM-powered applications in enterprise environments. Strong preference will be given to candidates located in Atlanta, GA, with consideration for candidates located in Washington, DC. What You'll Do * Design, develop, and enhance production generative AI applications and AI-enabled web solutions. * Build RAG solutions, enterprise knowledge assistants, conversational AI applications, chatbots, and agentic workflows. * Develop AI solutions using Azure AI Foundry, Azure OpenAI, Foundry Agent Service, and related Azure services. * Design agent and LLM workflows incorporating tool and function calling, structured outputs, guardrails, orchestration, and human-in-the-loop review. * Integrate AI applications with REST APIs, enterprise data sources, databases, cloud services, and MCP-enabled tools. * Develop secure, cloud-native backend services and web applications using Python, modern web frameworks, containers, and cloud services. * Implement and support multi-agent workflows that coordinate models, tools, data sources, and application services. * Test, evaluate, monitor, and optimize AI applications for response quality, reliability, latency, security, and cost. * Apply modern software engineering practices, including Git-based development, code reviews, automated testing, CI/CD, and Agile delivery. * Partner with engineering, architecture, data, cloud, and DevSecOps teams to deliver secure, scalable, and maintainable production AI solutions. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [GitOps for the people](https://www.wearedevelopers.com/videos/461-gitops-for-the-people) - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [One AI API to Power Them All](https://www.wearedevelopers.com/videos/1601-one-ai-api-to-power-them-all) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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