Agentic Artificial Intelligence (AI) Scientist

Overview

The Agentic Artificial Intelligence (AI) Scientist will serve as a technical expert in the design,
development, evaluation, and deployment of trustworthy AI agents and agentic AI systems. The
successful candidate will contribute to cutting-edge research focused on supporting the
development of methodologies, benchmarks, and best practices that enable the safe, secure,
reliable, and effective use of AI agents across a range of application domains.
The position will support research activities related to AI agents, multi-agent systems, tool-using
AI systems, human-AI collaboration, and emerging agentic AI architectures. The successful
candidate will also contribute to the transition of research outcomes into practical solutions,
guidance, and standards-related activities that advance trustworthy and responsible adoption of
agentic AI technologies.

Qualifications

• Experience conducting research and measurement science in artificial intelligence, machine learning, large language models (LLMs), agentic AI, multi-agent systems, or related fields.
• Experience designing, developing, evaluating, or deploying AI agents, autonomous systems, retrieval-augmented generation (RAG) systems, tool-using AI systems, or LLM- based applications.
• Experience developing benchmarks, evaluation methodologies, testbeds, frameworks, or pilot implementations for AI systems.
• Demonstrated ability to transition research outcomes into practical applications that deliver measurable impact to industry or government stakeholders.
• Familiarity with AI orchestration frameworks, agent architectures, human-AI interaction, AI safety, AI security, or autonomous system evaluation.
• Strong analytical, technical, and communication skills, with the ability to collaborate effectively in multidisciplinary research environments.

Research Proposal

Key Responsibilities include, but are not limited to:
Technical Development and Implementation:

• Design, develop, and evaluate AI agents and agentic AI systems. Develop and implement architectures for autonomous and human-supervised AI agents, including multi-agent and tool-integrated systems.
• Build experimental platforms, prototypes, and proof-of-concept demonstrations to assess agentic AI capabilities and limitations.

Research and Technical Analysis:

• Conduct advanced research and technical analyses to develop and evaluate trustworthy approaches for agentic AI systems.
• Develop methodologies, benchmarks, testbeds, and measurement techniques to assess agent performance, reliability, safety, robustness, explainability, and human oversight.
• Investigate challenges associated with autonomous decision-making, agent coordination, tool use, planning, memory, and adaptive behavior.
• Evaluate risks and failure modes associated with agentic AI systems, including unintended actions, misuse, autonomy-related risks, and security vulnerabilities

Technical Collaboration and Coordination:

• Collaborate with researchers and technical experts across NIST and external partner organizations to advance the science and practice of trustworthy agentic AI.
• Evaluate emerging agentic AI technologies and assess their applicability to multidisciplinary use cases.

Technology Transition and Stakeholder Engagement:

• Support the transition of research outcomes into practical tools, frameworks, guidance documents, and operational capabilities for government and industry stakeholders.
• Engage with external partners to identify challenges, opportunities, and emerging requirements for AI agents and autonomous systems.