Senior Engineer, Local AI - Agents and Systems

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1

Senior Engineer to lead technical efforts in deploying advanced AI agent frameworks and local runtimes on Windows and NVIDIA GeForce RTX GPUs, ensuring open-source AI agents operate locally, safely, and efficiently on consumer PCs, forming the foundation of the desktop AI operating system.

What you'd actually do

  1. Act as the lead engineer for developing the agent frameworks natively on Windows environments. You will build the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
  2. Lead the engineering efforts to optimize the agent runtimes for Windows. You will ensure that autonomous agents operate within detailed, policy-based privacy and security frameworks (e.g., handling filesystem access, secure inference routing, and network egress).
  3. Partner closely with internal AI research teams, driver teams, and the open-source OpenClaw community. Ensure our consumer hardware provides an excellent ecosystem for autonomous agents.
  4. Foster a collaborative engineering culture by mentoring other engineers, establishing guidelines for AI agent deployment, and writing reliable, production-ready code.

Skills

Required

  • Windows OS internals
  • process isolation
  • sandboxing technologies
  • system-level security architecture
  • LLM inference pipelines
  • GPU-accelerated computing
  • local models on consumer-grade hardware
  • AI orchestration and agentic frameworks
  • multi-agent systems
  • C++
  • Python
  • virtualization
  • containerization
  • sandboxing tools

Nice to have

  • Nemoclaw
  • OpenClaw
  • Nemotron models
  • Ollama
  • Llama.cpp
  • vLLM
  • CUDA
  • TensorRT
  • Hermes
  • LangChain

What the JD emphasized

  • lead engineer
  • technical roadmap
  • optimize the agent runtimes
  • policy-based privacy and security frameworks
  • open-source OpenClaw community
  • mentoring other engineers
  • AI agent deployment
  • production-ready code
  • 10+ years of relevant professional software engineering experience
  • at least 3+ years in Staff, or Lead Architect role
  • Deep understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security architecture
  • Proven understanding of LLM inference pipelines
  • GPU-accelerated computing
  • experience running local models on consumer-grade hardware
  • Practical experience with modern AI orchestration and agentic frameworks
  • understanding of how multi-agent systems plan, act, and use tools
  • Proficiency in multiple languages, particularly C++
  • Python
  • Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem

Other signals

  • Deploying advanced AI agent frameworks
  • local runtimes on Windows and NVIDIA GeForce RTX GPUs
  • open-source AI agents operate locally, safely, and efficiently on consumer PCs
  • desktop AI operating system