Principal Engineer - AI Agents and Systems

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1

Principal Engineer to lead the deployment of advanced AI agent frameworks and local runtimes on Windows and NVIDIA GPUs, focusing on open-source agents, local inference, privacy, and security for consumer PCs.

What you'd actually do

  1. Act as the lead architect for deploying the NemoClaw framework natively on Windows environments.
  2. Guide the engineering efforts to optimize the agent runtimes for Windows.
  3. Design the integration of NemoClaw with NVIDIA's hardware and middleware stack.
  4. Partner closely with internal AI research teams, driver teams, and the open-source OpenClaw community.
  5. Foster a collaborative engineering culture by mentoring senior engineers, establishing best practices for AI agent deployment, and writing reliable, production-ready code.

Skills

Required

  • C++
  • Python
  • TypeScript
  • 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

Nice to have

  • Open-source AI agent platforms
  • NVIDIA GeForce RTX architecture
  • virtualization
  • containerization
  • robust sandboxing tools
  • technical community engagement

What the JD emphasized

  • 15+ years of relevant professional software engineering experience
  • at least 3+ years in a Principal, 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 (Ollama, Llamacpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware.
  • Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, LangChain, AutoGPT) and an understanding of how multi-agent systems plan, act, and use tools.

Other signals

  • Deploying advanced AI agent frameworks
  • Local runtimes to Windows and NVIDIA GeForce RTX GPUs
  • Open-source AI agents run locally, safely, and efficiently
  • Desktop AI operating system