Senior Product Manager, Local AI and Agents for Enterprise

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Product Manager for local AI and agents on Linux for enterprise, focusing on defining agent use cases, owning the product strategy for Linux developer experience, and collaborating with inference backend teams. Requires strong AI/ML and developer tools experience, with a focus on enterprise deployments and modern AI workflows.

What you'd actually do

  1. Define and lead the enterprise agent use case — understand how enterprises deploy agents on-prem, what they need from the platform, and where NVIDIA should invest.
  2. Collaborate with Product Managers that are working on cloud inference backends (vLLM, SGLang, TensorRT-LLM, and PyTorch) to drive and prioritize requirement for local AI.
  3. Own the product strategy and roadmap for the Linux developer experience on NVIDIA client platforms (DGX Spark, DGX Station, RTX PRO workstations, RTX Spark).
  4. Research the developer and enterprise AI ecosystem: interview customers, build personas and user journeys, and map workflows across training, fine-tuning, inference, and agent deployment.
  5. Work hands-on with the latest models, frameworks, and agent tooling so you can represent the developer's point of view in every decision.

Skills

Required

  • 8+ years of product management experience, with meaningful time on AI/ML, developer tools, or infrastructure products.
  • First-hand experience as a developer or engineer — you have shipped code in production and can debug a CUDA, PyTorch, or Docker issue alongside an engineer, not just manage around it.
  • Deep familiarity with modern AI workflows: training and fine-tuning, inference serving, agent frameworks, RAG pipelines, and evaluation.
  • Working knowledge of at least one major inference backend (vLLM, SGLang, TensorRT-LLM, or PyTorch-based serving).
  • Fluency in Linux as a development and deployment environment.
  • Strong written communication and the ability to translate technical depth for both engineers and executives.
  • Bachelor's degree in Computer Science, Electrical Engineering, or equivalent experience.

Nice to have

  • Prior role as an AI/ML engineer, inference systems engineer, or application developer building with LLM APIs and agent frameworks (LangChain, LlamaIndex, MCP).
  • Experience with model optimization — quantization, distillation, speculative decoding, KV-cache strategies.
  • Hands-on with CUDA, Triton, or low-level GPU programming.
  • Background in enterprise software, on-prem deployments, or private AI.
  • Open-source contributions to AI/ML, inference, or agent projects.

What the JD emphasized

  • First-hand experience as a developer or engineer
  • Deep familiarity with modern AI workflows: training and fine-tuning, inference serving, agent frameworks, RAG pipelines, and evaluation.
  • Working knowledge of at least one major inference backend (vLLM, SGLang, TensorRT-LLM, or PyTorch-based serving).

Other signals

  • Define and lead the enterprise agent use case
  • Own the product strategy and roadmap for the Linux developer experience on NVIDIA client platforms
  • Work hands-on with the latest models, frameworks, and agent tooling
  • Influence NVIDIA's GPU, system, and software roadmaps