Senior Product Manager, Agent Optimization

NVIDIA•Santa Clara, CA

1d•$208,000 - $379,500

About The Position

NVIDIA is seeking a Senior Product Manager to lead its applied research-to-product pipeline for agent optimization. The role spans initiatives to improve agent quality, cost efficiency, and safety, including finding useful signals in large-scale trace datasets, creating trustworthy custom evaluations for production agents, and applying continual learning to improve agent harnesses and model behavior. The position turns fast-moving research and early partner collaborations into open-source tools for diagnosing, evaluating, and improving agents. The Product Manager will own product strategy and roadmaps for a portfolio of projects, define outcomes and quality bars with research and engineering, and work with agent builders, observability and evaluation providers, and other partners. The role also shapes developer experiences and product interfaces, improves tool reliability and interoperability, builds adoption approaches with marketing and go-to-market teams, and establishes product messaging. Success is assessed through research and product results, partner outcomes, open-source adoption, and publications.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related field, or equivalent experience.
12 or more years of product management or closely related experience building technically sophisticated, zero-to-one AI or developer products.
Track record of turning ambiguous research or emerging technical capabilities into adopted products through partnerships, integrations, or open source.
Technical fluency in agent architectures, observability, evaluation design, and automated experimentation techniques.
Ability to independently engage mature customers and ecosystem partners, recruit design partners, uncover production constraints, and guide go-to-market teams through emerging zero-to-one projects.
Ability to build positive relationships with engineering and research teams, ask sharp questions, convert uncertainty into decisions, and support teams without prescribing implementation.
Evidence-driven product approach grounded in reproducible benchmarks, explicit success criteria, and clear judgment about which claims results support.
Excellent written and verbal communication, portfolio-level prioritization, and ability to align senior technical and business leaders around a clear product narrative.

Nice To Haves

Experience building agent infrastructure, AI observability, evaluation, optimization, or developer tooling at a frontier AI lab or high-caliber startup.
Direct experience designing benchmarks, evaluation systems, or experimentation approaches, or contributing to research publications for AI products.
Track record with open-source communities, SDKs, platform integrations, or developer ecosystems.
Hands-on familiarity building production agents and improving them on both quantitative and qualitative dimensions.

Responsibilities

Drive product strategy and roadmaps for portfolio projects, setting priorities, quality bars, and clear product outcomes with research and engineering teams.
Work with agent builders, observability and evaluation providers, and other partners to secure early-access engagements, support joint research and integrations, and convert market feedback into research directions and stronger product capabilities.
Partner with engineering and research teams to turn new findings and techniques into usable products and features.
Define developer experiences and product interfaces for open-source tools in the portfolio.
Work with engineering and adjacent product teams to improve reliability, usability, documentation, benchmark coverage, and interoperability among tools.
Build adoption motions with Product Marketing, Solution Architects, and go-to-market teams; identify qualified partners and workloads, guide pilots, and develop repeatable adoption playbooks.
Establish messaging and a narrative for agent optimization and continuous improvement loops, and clarify the distinct value of each product with Product Marketing.
Define and review evidence of success across research results, product results, partner outcomes, open-source adoption, and publications.
Own portfolio outcomes and decide what to scale, change, stop, or incubate next.