> Markdown version of [/jobs/ext/3730587-ai-engineer](https://www.wearedevelopers.com/jobs/ext/3730587-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). --- # AI Engineer - **Company:** Nou Systems Inc - **Location:** Huntsville, AL, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Ubuntu (Operating System), Continuous Integration, Custom Software, Data Stores, Linux, DevOps, Python (Programming Language), Machine Learning, Scrum Methodology, Software Architecture, E2e Testing, Software Engineering, Pytorch, Retrieval-Augmented Generation, Large Language Models, Llamaindex, Generative AI, Gitlab, Git, Information Technology, Production Code, Data Management, Software Version Control, Software Usability, Docker, ChromaDB - **Published:** October 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=2afd120732ebd44a ## About the Role * Bachelor's degree in Machine Learning, Computer Science, Software Engineering, or related technical field, with a Master's or higher preferred. * 5+ years of professional experience in AI/ML engineering, with 2+ years focused on LLMs or similar generative models. * Must possess or be able to obtain an active Secret Security Clearance. * U.S. Citizen., * Experience with newer approaches to using LLMs as a natural language interface to a data store (not just traditional RAG). * Experience with developing MCP tooling for custom applications. * Comfortable developing in a containerized (Docker) Linux-based (Ubuntu) environment. * Experience developing for a Continuous Integration/Continuous Development (CI/CD) pipeline. * Active Top Secret clearance. ## Description Our team is developing Government Off-the-Shelf software that has an existing customer base, is currently in use in ongoing warfighting exercises, and has a years-long product roadmap. We're seeking an AI engineer who can help prototype new LLM-powered capabilities and integrate those capabilities into this software. You'll be an integral part of a multidisciplinary software team combining a web-based front end, large-data-management back end, and on-prem LLM-powered data exploration. We're looking for an engineer who understands not only the under-the-hood details of LLMs but also how to use them in production code, and who strikes a balance between cutting-edge research and achievable, usable software at a fast tempo. We need people who enjoy working in tandem with other talented developers, architects, QA, and integration/DevOps, and who rise to the challenge of team communication and cohesion in an Agile/SAFe team. We want people who are passionate about the quality of software we deliver. You'll need to be comfortable with developing capabilities that are delivered to end users on a 10-week cadence, helping elicit end user needs rather than being handed a pile of DOORS-managed requirements, and scoping work even in the absence of perfect information., * Proficiency in Python + PyTorch, generative AI frameworks (LangChain, LlamaIndex), and vector databases (ChromaDB). * Software development as an individual contributor without agentic coding support. * Production code: modular, unit tested, supports integration and end-to-end testing, maintained in source control (Git + GitLab). * Scrum Agile software development, including being active in ceremonies (standup, sprint reviews, Product Increment planning). * Team-focused development: ticket management, constructive peer reviews, backlog management. Core Skills: * Evaluate changing AI landscape: help us intelligently decide what new technologies and frameworks to incorporate through comprehensive analysis of alternatives. * Mentor and lead technical contributors: be a force multiplier. * Support software architecture development: contribute to our product's overall structure in support of our Chief Architect. * Strong communication and collaboration skills: communicate your technical decisions, back them up with quantitative information, and flex with the needs of the wider team and project when necessary.