NVIDIA is a leading technology company, and they are seeking a Product Manager to lead strategic AI platform initiatives across infrastructure, silicon, and developer experience. The role involves defining product vision and execution, driving roadmap planning, and enhancing developer productivity through AI-powered capabilities.
Responsibilities:
- Define product strategy and execution across a portfolio of AI platform initiatives, translating ambiguous technical challenges into clear problem statements, product direction, and prioritized roadmaps
- Develop deep empathy for internal developers and engineering teams through direct engagement, turning user challenges into intuitive, high-impact platform capabilities
- Drive roadmap planning across short- and long-term horizons, balancing customer impact, technical feasibility, scalability, and strategic business priorities
- Identify and evaluate high-value opportunities for AI-powered tooling, agentic automation, and developer productivity improvements, with a strong focus on measurable adoption and operational impact
- Establish product success metrics and use data-driven insights to continuously refine prioritization, feature scope, and user experience
- Champion developer experience and UX quality by understanding real engineering workflows, trust dynamics in AI-assisted tooling, and the factors that drive sustained platform adoption
- Communicate product strategy, trade-offs, and execution plans clearly across technical and executive audiences, influencing decisions at all levels of the organization
- Lead cross-functional collaboration across engineering, infrastructure, architecture, and design teams, driving alignment and execution in a highly matrixed environment
Requirements:
- BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience
- 12+ years of product management experience building developer platforms, infrastructure products or AI/ML systems at scale
- Experience leading products that incorporate LLM-powered agents, autonomous workflows or AI-accelerated developer experiences
- Strong technical depth in AI/ML infrastructure, including distributed training, inference optimization, GPU-accelerated computing, and large-scale systems performance
- Experience defining and delivering observability, telemetry, profiling, or performance tooling for engineering organizations
- Proven experience in fostering adoption of complex developer-facing products across large organizations
- Deep familiarity with modern SDLC tooling and developer workflows across build, test, deployment, and runtime environments
- Outstanding systems thinking with capacity to reason across the stack - from hardware and infrastructure layers through APIs, platforms, and end-user developer experiences
- Excellent written and verbal communication; able to distill ambiguous technical problems into clear product narratives
- Background in semiconductor, hardware, or systems software companies
- Experience driving enterprise quality AI product adoption - defining UX, measuring engagement, and working with internal champions