Artificial Intelligence (AI) Engineer (Partial Telework)

GliaCell Technologies•Annapolis Junction, MD

3d•$170,000 - $260,000•Hybrid

About The Position

GliaCell is seeking an AI Engineer to join one of their subcontracts, supporting a U.S. Government customer. This full-time position involves providing technical expertise to sustain critical mission-related software and systems for a large government contract. The role is part of the Report Authoring and Dissemination (RAD) team, focusing on designing, prototyping, and integrating AI-enabled capabilities into the existing RAD architecture. The primary focus is on applying existing large language models (LLMs) to real mission workflows, rather than training new models. The AI Engineer will build agentic solutions, which are systems of coordinated AI agents and prompts, to automate tasks, streamline workflows, and enhance intelligence operations.

Requirements

Possess an active or rein-statable TS/SCI with Polygraph security clearance.
An active Top Secret clearance with polygraph (CI within the last 7 years).
9 years of relevant experience with a bachelor's degree, or 7 years of relevant experience with a master's degree.
U.S. Citizenship.
Works well independently as well as on a team.
Strong communication skills.
Strong Python development skills, with experience writing production-quality, maintainable code
Hands-on experience building applications on top of existing LLMs (e.g., via APIs for commercial or self-hosted models)
Experience designing multi-agent or multi-step AI workflows, including prompt chaining, tool use, and agent orchestration (e.g., LangChain, LlamaIndex, or custom frameworks)
Strong prompt engineering skills and experience evaluating/validating LLM outputs
Experience integrating AI capabilities into existing software architectures (RESTful APIs, microservices)
Experience with the Amazon Web Services (AWS) cloud computing platform

Nice To Haves

Experience with retrieval-augmented generation (RAG) pipelines and vector databases
Familiarity with LLM observability and evaluation tooling
Experience conducting exploratory data analysis on structured and unstructured datasets to prepare inputs for AI workflows
Familiarity with MLOps/LLMOps practices for deploying and monitoring AI capabilities at scale
Familiarity with domain knowledge surrounding government agency reporting and dissemination policies

Responsibilities

Lead the design and development of AI-driven solutions from conception to deployment, building multi-agent workflows in which coordinated agents and prompts work together to produce outputs supporting reporting and dissemination. This includes prototyping, writing production-quality code, and maintaining deployed AI capabilities.
Integrate existing foundation models into the RAD architecture via APIs and orchestration frameworks, selecting the right model and approach for each task rather than building models from scratch.
Design, test, and refine prompts and agent instructions to reliably automate manual tasks, and decompose complex mission workflows into discrete steps an agent pipeline can execute.
Develop robust testing, evaluation, and validation strategies for AI-generated outputs, ensuring accuracy, consistency, and appropriate handling of edge cases before outputs reach analysts and reports.
Serve as a key technical liaison, collaborating with cross-functional teams including system engineers, software developers, and domain experts. Effectively present and articulate recommended AI approaches, discussing the tradeoffs and implications of different implementations with both technical and non-technical stakeholders.
Stay current with the rapidly evolving LLM and agentic AI landscape (new models, orchestration frameworks, and tooling), continuously identifying practical opportunities to apply emerging capabilities to the system.