Senior Engineer, Local AI - Agents and Systems

NVIDIA•Redmond, CA

About The Position

Artificial intelligence is shifting from passive help to autonomous, always-on workflows. Our mission is to make this change seamless, efficient, and secure for millions globally. We seek a Senior Engineer to lead technical efforts in deploying advanced AI agent frameworks and local runtimes on Windows and NVIDIA GeForce RTX GPUs. You will guide development so open-source AI agents (such as Nemoclaw and OpenClaw) operate locally, safely, and efficiently on consumer PCs. By combining powerful local inference (Nemotron models) with strong privacy routers and sandboxed execution, you will help develop the foundation of the desktop AI operating system.

Requirements

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.

Responsibilities

Act as the lead engineer for developing the agent frameworks natively on Windows environments.
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.
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.