NVIDIA
AI Software Platforms
ProductManager,AIPlatformSW-AgenticAIKernelGeneration
Neural analysis suggests this role is
optimal for Senior candidates.
“Product Manager, AI Platform SW - Agentic AI Kernel Generation at NVIDIA. Skills: AI Platform SW, Agentic AI Kernel Generation, Product Management, AI Agents, LLM-based coding workflows. Crafting AI kernels that connect data pipelines, evaluation suites, and GPU-accelerated runtimes. Architecting agent-focused products that let coding agents generate, refactor, and optimize CUDA kernels and graph-level execution plans across diverse GPU architectures”
What You'll Achieve.
Enable developers to be successful on the NVIDIA platform; Safely release faster, better-performing inference and training solutions
Industry & Context.
What They're Looking For.
Must Have
7+ years of technical product management or closely related experience shipping developer or platform products in AI, ML infrastructure, or high-performance, 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, Worked on connecting agents to compilers or execution environments, Proven record of crafting and releasing automated testing or evaluation suites, BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing architectures and systems
Nice to Have
PhD or equivalent experience in Computer Engineering, Computer Science, or another technical specialty, Track record building or launching coding-agent platforms or copilots used by development teams at scale, Contributions to performance-critical open-source projects (e. g. , Triton, TVM, FlashAttention, kernel libraries, agent frameworks) with clear community adoption and impact, Research experience in GPU kernel optimization, collective or group communication algorithms, multi-agent systems, or ML model serving / inference architectures, Experience crafting cost-per-inference or cost-per-token models that incorporate hardware utilization, energy efficiency, and cluster scaling, and using those models to guide product strategy and tradeoffs
What You'll Do.
Crafting AI kernels that connect data pipelines
and GPU-accelerated runtimes
Architecting agent-focused products that let coding agents generate
and optimize CUDA kernels and graph-level execution plans across diverse GPU architectures
Defining the end-to-end data lifecycle for agent training and evaluation
including dataset curation
artificial data creation
and benchmark suites for correctness
and compiler engineering teams to integrate agents with compilers
and runtimes in a safe
Driving multi-agent orchestration
prioritizing features
and delivering launches and messaging for agentic AI kernel generation
How You'll Work.
Team & Collaboration
Partner closely with engineering, research, and customers; Partner with CUDA, kernel, and compiler engineering teams; Collaborate with internal and external developers, NVIDIA leaders, and ecosystem partners
Process & Methodology
Develop roadmaps, Prioritize features, Deliver launches
Full Job Description
NVIDIA's AI Software Platforms team is building the next generation of agentic AI infrastructure that lets coding agents synthesize, optimize, and deploy GPU kernels automatically. This job focuses on crafting AI kernels that connect data pipelines, evaluation suites, and GPU-accelerated runtimes. This helps developers safely release faster, better-performing inference and training solutions. As Product Managers at NVIDIA, we enable developers to be successful on the NVIDIA platform and push the boundaries of what is possible with AI deployments. In this role, you will act as the internal champion for AI agents and LLM-based coding workflows that generate optimized kernels. You'll partner closely with engineering, research, and customers to define strategy, develop roadmaps, and build products that span the entire agent lifecycle — from data collection and synthetic data generation to evaluation, deployment, and continuous improvement. **What you 'll be doing:** * 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
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