Generative AI Engineer

This role focuses on researching, developing, evaluating, and integrating generative AI and agentic AI capabilities to support complex mission needs across U.S. Government agencies. You will provide technical leadership, build prototypes using mission-relevant data, and evaluate solutions using MITRE platforms and hardware.

What You Will Do

• Provide technical leadership to cross-functional teams developing and implementing AI solutions, including prototype implementations leveraging generative AI, large language model technology, and agentic AI capabilities.
• Analyze data and language processing needs and recommend innovative approaches to address mission-critical problems.
• Prototype AI/GenAI systems or components based on workflow and operational mission requirements, then deliver prototypes into operational spaces or systems using real mission-relevant data.
• Evaluate technology solutions in the context of mission data and workflow needs, and provide actionable recommendations toward workable solutions for critical problems.
• Convey complex technical concepts to non-technical audiences through briefings and/or white papers.
• Lead or contribute to small technical teams to address technical challenges by applying GenAI capabilities.
• Leverage MITRE’s Federal AI Sandbox using NVIDIA DGX SuperPod hardware and the AI Platform to support research, development, and evaluation of generative AI capabilities.

Required Qualifications

• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 3 years with a Master’s degree; or a PhD with relevant experience who can immediately contribute; or an equivalent combination of related education and work experience.
• Demonstrated recent experience applying large language model (LLM) technology in R&D or operational settings.
• Demonstrated experience prototyping or developing AI components or systems aligned with department capabilities.
• Ability to apply state-of-the-art machine learning techniques to data and natural language processing challenges.
• Experience with Python and Linux, plus SQL, and tools or libraries including pandas, numpy, scikitlearn, and pytorch.
• Ability to work independently to learn new technologies, methods, processes, frameworks, or platforms.
• Excellent written and verbal communication skills for articulating challenging technical concepts to lay and expert audiences.
• Eligibility to obtain and maintain a Top Secret U.S. Government issued Security Clearance, including being a U.S. Citizen.
• Minimum 3 days per week on-site.

Technologies and Tools

• Generative AI, agentic AI, large language model (LLM) technology, and AI/GenAI
• Python, Linux, SQL
• pandas, numpy, scikitlearn, pytorch
• NVIDIA DGX SuperPod hardware and MITRE AI Platform

Preferred Qualifications

• Advanced degree in computer science, engineering, computational linguistics, or a related discipline.
• Track record of successful deployment of AI/HLT systems or components used by customers or stakeholders outside of a lab or experimental setting.
• Active DOW Secret or Top Secret security clearance.

Role Details

• Location: Bridgeport, WV (onsite)
• Salary range: USD 143,600 - 215,400 per year
• Compensation midpoint: $179,500 (range: $143,600 - $179,500 - $215,400 Annual)
• Security clearance: Top Secret required or must be obtained within one year from the date of hire

Department Overview

The Generative and Agentic AI Engineering Department works across the full range of U.S. Government agencies to develop, engineer, and deploy advanced AI capabilities for sponsors. The department applies generative AI, agentic AI, and AI/ML research and engineering to operational challenges, including researching, prototyping, and transitioning technologies to support mission objectives.

Work includes generative AI applications, agentic AI system design, AI model fine-tuning and adaptation, knowledge representation and extraction, AI architectures, and MLOps/LLMOps, alongside human language technology (HLT). The department maintains expertise in large language models, agentic AI, autonomous AI workflows, data processing pipelines, computational linguistics, knowledge graph construction, identity resolution, and AI/GenAI evaluation.