# Senior Product Manager, Agent Optimization at NVIDIA

NVIDIA is hiring a Senior Product Manager, Agent Optimization in Santa Clara, United States. It pays $208k-$328k a year and Level rates it Works on AI ●●●○; you can [apply on NVIDIA](https://jobsbylevel.com/go/95860785-2084-4c37-9d0b-4c6bb417691d?utm_medium=ai-agent).

AI Level 3, AI centrality 65 out of 100. US, CA, Santa Clara.

## Details

- Company: [NVIDIA](https://jobsbylevel.com/companies/nvidia)
- AI level: AI Level 3 (score 65 out of 100)
- Location: US, CA, Santa Clara
- Salary: $208k-$328k
- Posted: October 2, 2026
- Apply: https://jobsbylevel.com/go/95860785-2084-4c37-9d0b-4c6bb417691d?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-product-manager-agent-optimization-at-nvidia-0e32ad

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/senior-product-manager-agent-optimization-at-nvidia-0e32ad

## Description

NVIDIA needs a Senior Product Manager to lead our applied research-to-product pipeline for agent optimization. Our applied AI research engineering team invests in multiple areas related to optimizing agents for improved quality, cost efficiency, and safety. Projects include helping developers find important signals in large-scale trace datasets, crafting trustworthy custom evals for production agents, and continual learning to improve harness and model behavior. Manage fast paced research and early partner collaborations into open source tools that impact how agents are diagnosed, evaluated, and improved across the industry! What you’ll be doing: Drive the product strategy and relevant roadmaps for specific projects in your portfolio. Set priorities, quality bars, and clear product outcomes together with research & engineering teams. Work directly with agent builders, observability and eval tool providers, and other partners to secure early-access engagements, make joint research & integrations successful, and turn market feedback into research directions and stronger product capabilities. Partner with engineering & research to translate new findings and techniques into usable products and features. Define the developer experience and product interfaces for relevant open source tools in your portfolio. Partner with engineering and adjacent product teams to improve reliability, usability, documentation, benchmark coverage, and how multiple tools work together. Build the adoption motion with Product Marketing, Solution Architects, and GTM teams. Identify qualified partners and workloads, guide pilots, and create repeatable adoption playbooks. Establish the messaging and narrative for how our teams talk about agent optimization and continuous improvement loops. Clarify the distinct value of each product in your portfolio together with Product Marketing. Define and inspect the evidence for success across research results, product results, partner outcomes, open source adoption, and publications. Own the outcomes and decide what to scale, change, stop, or incubate next. What we need to see: Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related field, or equivalent experience. 12+ years of product management or closely related experience building technically sophisticated, zero-to-one AI or developer products. A record of turning ambiguous research or emerging technical capabilities into adopted products through a partnership motion, integrations, or open source. Technical fluency in agent architectures, observability, evaluation design, and automated experimentation techniques. Ability to engage mature customers and ecosystem partners independently, recruit design partners, uncover real production constraints, and guide GTM teams through emerging zero-to-one projects. Positive relationship with Engineering and Research teams. Ask sharp questions, convert uncertainty into decisions, and support teams without prescribing implementation. An evidence-driven product approach grounded in reproducible benchmarks, explicit success criteria, and clear judgment about which claims the results support. Excellent written and verbal communication, portfolio-level prioritization, and the ability to align senior technical and business leaders around a clear product narrative. Ways to stand out from the crowd: Experience building agent infrastructure, AI observability, evaluation, optimization, or developer tooling at a frontier AI lab or high-caliber startup. Direct experience designing benchmarks, eval systems, experimentation approaches, or contributing to research publications for AI products. A track record with open-source communities, SDKs, platform integrations, or developer ecosystems. Hands-on familiarity building production agents and successfully improving them on both quantitative and qualitative dimension. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered

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