Senior Engineer - AI Agents and Systems

NVIDIA•Redmond, WA

About The Position

Artificial intelligence is moving from passive assistance to autonomous, always-on agentic workflows. Our mission is to make this transition flawless, high-performing, and secure for millions of users worldwide. We are looking for a Senior Engineer to serve as a key technical leader in deploying advanced AI agent frameworks and local runtimes to Windows and NVIDIA GeForce RTX GPUs. You will lead the development to ensure open-source AI agents (like Nemoclaw and OpenClaw) run locally, safely, and efficiently on consumer PCs. By combining powerful local inference (Nemotron models) with robust privacy routers and sandboxed execution, you will help create 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, 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, 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.
Shape 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 thorough, 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 best practices for AI agent deployment, and writing reliable, production-ready code.