Principal 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 Principal 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

Experience: 15+ years of relevant professional software engineering experience, with at least 3+ years in a Principal, Staff, or Lead Architect role.
Education: BS, MS, or PhD in Computer Science, Computer Engineering, or a related technical field (or equivalent experience).
Systems & OS Knowledge: Deep understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security architecture.
AI & GPU Infrastructure: Proven understanding of LLM inference pipelines (Ollama, Llamacpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware.
Agentic Frameworks: 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.
Programming Languages: Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration), Python (for AI/blueprint logic), and TypeScript (for agent plugins and tooling).
Communication: Strong ability to translate sophisticated architectural concepts into clear technical documentation and communicate effectively across diverse engineering teams.

Nice To Haves

Demonstrated experience contributing to open-source AI agent platforms or orchestration tools (especially OpenClaw).
Extensive knowledge of the NVIDIA GeForce RTX architecture and its specific constraints and advantages for edge AI.
Previous experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.
Active engagement in the technical community (blogs, talks, whitepapers) focusing on the intersection of AI, security, and local compute.

Responsibilities

Technical Architecture & Strategy: Act as the lead architect for deploying the NemoClaw framework natively on Windows environments. You will shape the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
Systems-Level Sandboxing: Guide the engineering efforts to optimize the agent runtimes for Windows. You will ensure that autonomous agents operate within thorough, policy-based privacy and security frameworks (e.g., handling filesystem access, secure inference routing, and network egress).
Performance Optimization: Design the integration of NemoClaw with NVIDIA's hardware and middleware stack. You will work to minimize latency and memory footprint, ensuring local models (like Nemotron) run efficiently on GeForce GPUs using TensorRT and CUDA. 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.
Mentorship & Team Support: Foster a collaborative engineering culture by mentoring senior engineers, establishing best practices for AI agent deployment, and writing reliable, production-ready code.