AI ENGINEER

Type of Requisition: Regular Clearance Level Must Currently Possess: Top Secret SCI + Polygraph Clearance Level Must Be Able to Obtain: Top Secret SCI + Polygraph Public Trust/Other Required: None Job Family: Data Science and Data Engineering Job Qualifications: Skills: Agentic AI, AI Agents, Amazon Web Services (AWS) Certifications: None Experience: 5 + years of related experience US Citizenship Required: Yes Job Description: AI ENGINEER *** Up to 3 Days per week telework! *** Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges as an AI Engineer. MEANINGFUL WORK AND PERSONAL IMPACT As an AI Engineer, the work you’ll do at GDIT will be impactful to the mission of a mission-critical customer. You will play a crucial role in designing, prototyping, and integrating AI-enabled capabilities into an existing mission - critical tool. ● Support the application of existing large language models (LLMs) to real mission workflows rather than training new models. ● Collaborate with system and software engineers ● Build agentic solutions, systems of coordinated AI agents and prompts that automate tasks currently performed manually, streamline authoring and reporting workflows, and enhance the overall effectiveness of intelligence operations. WHAT YOU’LL NEED TO SUCCEED Bring your expertise and drive for innovation to GDIT. Th [... source excerpt omitted ...] ave: ● Education: Bachelor of Arts/Bachelor of Science ● Experience: 8+ years of related experience ● Security clearance level: TS/ SCI W/ Polygraph ● US citizenship required Responsibilities: Agentic Solution Design & Development: 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. LLM Integration: Integrate existing foundation models into the RAD architecture via APIs and orchestration frameworks, sel [... source excerpt omitted ...] ntinuously identifying practical opportunities to apply emerging capabilities to the system. Required Technical 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, m