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Senior Engineer, Local AI - Agents and Systems

NVIDIA· Engineer, Sys SW
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Santa Clara, CA, Redmond, WA$184k - $287.5k + equityfull-timePosted 3w ago

About the role

Lead engineer to deploy advanced AI agent frameworks and local runtimes on Windows and NVIDIA GeForce RTX GPUs, enabling open-source AI agents to operate locally on consumer PCs with strong privacy and security, forming the desktop AI operating system foundation.

Responsibilities

  • 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.
  • 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).
  • 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.
  • Foster a collaborative engineering culture by mentoring other engineers, establishing guidelines for AI agent deployment, and writing reliable, production-ready code.

Qualifications

  • 10+ years of relevant professional software engineering experience, with at least 3+ years in Staff, or Lead Architect role.
  • BS, MS, or PhD in Computer Science, Computer Engineering, or a related technical field (or equivalent experience).
  • Deep understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security architecture.
  • Proven understanding of LLM inference pipelines (Ollama, Llama.cpp, 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, Hermes, LangChain) and an understanding of how multi-agent systems plan, act, and use tools.
  • Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration) and Python (for AI/blueprint logic).
  • Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.

Skills

Required:Windows OS internalsLLM inference pipelinesGPU-accelerated computingAI orchestration / agent frameworksC++ and Python

Benefits

  • Equity and benefits package. See NVIDIA benefits portal.
Last updated Oct 2, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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