Product Manager, AI Platform SW - Agentic AI Kernel Generation

Responsibilities

• We architect agent-focused products that let coding agents generate, refactor, and optimize CUDA kernels and graph-level execution plans across diverse GPU architectures.
• Define the end-to-end data lifecycle for agent training and evaluation, including dataset curation, artificial data creation, and benchmark suites for correctness, latency, and adaptability.
• Partner with CUDA, kernel, and compiler engineering teams to integrate agents with compilers, profilers, execution sandboxes, and runtimes in a safe, observable way.
• We collaborate with internal and external developers, NVIDIA leaders, and ecosystem partners to drive multi-agent orchestration, prioritize features, and deliver launches and messaging for agentic AI kernel generation.
• What we need to see
• 7+ years of technical product management or closely related experience shipping developer or platform products in AI, ML infrastructure, or high-performance computing; we care deeply about end-to-end ownership and impact.
• Proven experience in the AI agent or LLM space, including developing or productizing coding agents. Experience with multi-agent orchestration and self-healing or code loops that improve over time is required. Candidates should also have worked on connecting agents to compilers or execution environments.
• Proven record of crafting and releasing automated testing or evaluation suites. These suites measure agents on non-subjective metrics such as correctness, performance, and latency. We rely on data to guide both development and iteration.
• BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing architectures and systems.
• Ways to stand out from the crowd

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