Tech Stack
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.
AI @ 4
CUDA @ 4
GPU @ 4
LLM @ 4
LangChain @ 4
Python @ 6
Security @ 7
TensorRT @ 4
vLLM @ 6
- 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 shifting from passive help to autonomous, always-on workflows. NVIDIA seeks 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 local inference with Nemotron models, privacy routers, and sandboxed execution, you will help develop the foundation of a desktop AI operating system.
Responsibilities
- Act as the lead engineer for developing agent frameworks natively on Windows environments.
- Build the technical roadmap for bringing always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
- Lead efforts to optimize agent runtimes for Windows.
- Ensure autonomous agents operate within policy-based privacy and security frameworks, including filesystem access, secure inference routing, and network egress.
- Partner with internal AI research teams, driver teams, and the open-source OpenClaw community.
- Help ensure consumer hardware provides an excellent ecosystem for autonomous agents.
- Mentor other engineers, establish guidelines for AI agent deployment, and write reliable, production-ready code.
Requirements
- 12+ years of relevant professional software engineering experience, including at least 3+ years in a 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, including Ollama, Llama.cpp, and vLLM.
- Experience with GPU-accelerated computing, including CUDA and TensorRT, and running local models on consumer-grade hardware.
- Practical experience with modern AI orchestration and agentic frameworks, such as OpenClaw, Hermes, and LangChain.
- Understanding of how multi-agent systems plan, act, and use tools.
- Proficiency in multiple programming languages, particularly C++ for performance-critical systems and OS integration, and Python for AI and blueprint logic.
- Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.
Benefits
NVIDIA offers competitive salaries, a comprehensive benefits package, equity, and benefits for employees and their families. The base salary is determined by location, experience, and the pay of employees in similar positions. Applications will be accepted at least until August 2, 2026. NVIDIA is an equal opportunity employer.