Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
TypeScript @ 6
Python @ 6
Communication @ 7
Performance Optimization @ 4
LLM @ 4
CUDA @ 4
GPU @ 4
AI @ 4
vLLM @ 4
TensorRT @ 4
LangChain @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
Responsibilities
- Technical Architecture & Strategy: Act as the lead architect for deploying the NemoClaw framework natively on Windows environments. Shape the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
- Systems-Level Sandboxing: Guide engineering efforts to optimize the agent runtimes for Windows. Ensure autonomous agents operate within policy-based privacy and security frameworks (handling filesystem access, secure inference routing, and network egress).
- Performance Optimization: Design the integration of NemoClaw with NVIDIA's hardware and middleware stack. Minimize latency and memory footprint to ensure local models (like Nemotron) run efficiently on GeForce GPUs using TensorRT and CUDA.
- Cross-team Partnership: Partner closely with internal AI research teams, driver teams, and the open-source OpenClaw community to ensure consumer hardware provides an excellent ecosystem for autonomous agents.
- Mentorship & Team Support: Mentor senior engineers, establish best practices for AI agent deployment, and write reliable, production-ready code.
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.
Ways to Stand Out
- Demonstrated experience contributing to open-source AI agent platforms or orchestration tools (especially OpenClaw).
- Extensive knowledge of the NVIDIA GeForce RTX architecture and its 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.
Benefits
- Competitive base salary (see range below).
- Eligibility for equity and company benefits (link to benefits provided in the original posting).
Additional information
- Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.
- You will also be eligible for equity and benefits.
- Applications for this job will be accepted at least until April 17, 2026.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to diversity and inclusion.