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
Python @ 6
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. The mission is to make this transition flawless, high-performing, and secure for millions of users worldwide. This role serves as a key technical leader in deploying advanced AI agent frameworks and local runtimes to Windows and NVIDIA GeForce RTX GPUs. The engineer will lead 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 privacy routers and sandboxed execution to build the foundation of a desktop AI operating system.
Responsibilities
- Act as the lead engineer for developing AI agent frameworks natively on Windows environments and shape the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
- Lead engineering efforts to optimize agent runtimes for Windows, ensuring autonomous agents operate within policy-based privacy and security frameworks (e.g., filesystem access handling, secure inference routing, network egress control).
- Partner closely with internal AI research teams, driver teams, and the open-source OpenClaw community to ensure a robust consumer hardware ecosystem for autonomous agents.
- Mentor other engineers, establish best practices for AI agent deployment, and write reliable, production-ready code.
Requirements
- 10+ years of relevant professional software engineering experience, with at least 3+ years in Staff or Lead Architect roles.
- 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 (examples: Ollama, Llamacpp, vLLM) and experience running local models on consumer-grade hardware.
- Experience with GPU-accelerated computing (CUDA, TensorRT) and local model inference on GeForce RTX hardware.
- Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, Hermes, LangChain) and knowledge of multi-agent planning, acting, and tool usage.
- Proficiency in performance-critical languages and ecosystems, particularly C++ (for systems/OS integration) and Python (for AI/blueprint logic).
- Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.
Compensation and Benefits
- Base salary ranges by level:
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
- Eligible for equity and benefits. (Link to benefits referenced in the posting.)
Additional Information
- Applications for this job will be accepted at least until May 15, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer.