Post Bachelor
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.
Agentic Artificial Intelligence (AI) Scientist
- 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.
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.