NVIDIA

3 months ago

Product Manager, AI Platform SW - Agentic AI Kernel Generation

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 16 hours agoStatus: Live

Job Summary

Lead product strategy and roadmaps for agentic AI kernel generation on NVIDIA’s GPU platform. Own end-to-end lifecycle from data collection and synthetic data to evaluation, deployment, and continuous improvement, partnering with engineering, research, and customers to deliver scalable AI kernel generation workflows across multiple GPU architectures.

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Product Management

Seniority: Sr. Manager level

Key Responsibilities

•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.
•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.
•Own strategy and roadmaps for agent lifecycle products, from data collection to deployment and continuous improvement.

Key Requirements

•7+ years of technical product management or closely related experience shipping developer or platform products in AI, ML infrastructure, or high-performance computing; strong end-to-end ownership and impact.
•Proven experience in the AI agent or LLM space, including developing or productizing coding agents, with multi-agent orchestration and self-healing or code loops and connecting agents to compilers or execution environments.
•Proven record of crafting and releasing automated testing or evaluation suites that measure agents on objective metrics such as correctness, latency, and performance.
•BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing architectures and systems.
•Track record building or launching coding-agent platforms or copilots, with contributions to performance-critical open-source projects and clear community adoption.

Experience:7+ yearsAIML infrastructureGPU computing

Education:Bachelor's

Skills:CUDAGPUKernelsCompilersProfilersExecution sandboxesLLMAgentsMulti-agent orchestrationBenchmarkingData collectionSynthetic data

Tech Stack:CUDAGPUCompilersProfilersExecution sandboxesLLMAgentsMulti-agent orchestrationBenchmarks

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

3 months ago

Product Manager, AI Platform SW - Agentic AI Kernel Generation

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 16 hours agoStatus: Live

Job Summary

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Product Management

Seniority: Sr. Manager level

Key Responsibilities

•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.
•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.
•Own strategy and roadmaps for agent lifecycle products, from data collection to deployment and continuous improvement.

Key Requirements

•7+ years of technical product management or closely related experience shipping developer or platform products in AI, ML infrastructure, or high-performance computing; strong end-to-end ownership and impact.
•Proven experience in the AI agent or LLM space, including developing or productizing coding agents, with multi-agent orchestration and self-healing or code loops and connecting agents to compilers or execution environments.
•Proven record of crafting and releasing automated testing or evaluation suites that measure agents on objective metrics such as correctness, latency, and performance.
•BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing architectures and systems.
•Track record building or launching coding-agent platforms or copilots, with contributions to performance-critical open-source projects and clear community adoption.

Experience:7+ yearsAIML infrastructureGPU computing

Education:Bachelor's

Skills:CUDAGPUKernelsCompilersProfilersExecution sandboxesLLMAgentsMulti-agent orchestrationBenchmarkingData collectionSynthetic data

Tech Stack:CUDAGPUCompilersProfilersExecution sandboxesLLMAgentsMulti-agent orchestrationBenchmarks

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor