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, running natively on the GPUs already sitting in their PCs.
We are looking for a Senior Software Engineer to build and optimize the local runtimes and agent frameworks that bring autonomous AI to Windows and NVIDIA GeForce RTX GPUs. You will be a hands-on individual contributor responsible for making open-source AI agents (like NemoClaw and OpenClaw) run locally, safely, and efficiently on consumer PCs. By combining high-performance local inference (Nemotron models) with robust privacy routers and sandboxed execution, you will help build the foundation of the desktop AI operating system. This is a deeply technical, code-first role. You will spend your days profiling inference pipelines, squeezing latency and memory out of local models, and hardening agent runtimes.
What you will be doing:
Local Inference Optimization: Optimize performance of local LLMs (Nemotron and others) on GeForce RTX hardware. Profile and optimize inference across Ollama, llama.cpp, and vLLM, minimizing latency and memory footprint using TensorRT and CUDA.
Agent Runtime Engineering: Build and optimize agentic harnesses (NemoClaw, OpenClaw) to run natively and reliably on Windows. Implement the orchestration logic that lets multi-agent systems plan, act, and use tools efficiently on constrained consumer hardware.
Sandboxing & Security: Implement policy-based privacy and security frameworks for autonomous agents, handling filesystem access, secure inference routing, and network egress within thorough sandboxed execution environments.
Hardware/Software Integration: Work close to the metal, integrating agent and inference stacks with NVIDIA's driver and middleware layers to extract maximum performance from RTX GPUs.
Cross-Team Collaboration: Partner with internal AI research teams, driver teams, and the open-source OpenClaw community to ensure our consumer hardware is the best possible platform for local agents.
Code Quality: Write reliable, production-ready code, contribute to engineering best practices, and raise the technical bar through code review and design input.
What we need to see:
Experience: 12+ years of relevant professional software engineering experience, with a track record of shipping performance-critical systems.
Education: BS, MS, or PhD in Computer Science, Computer Engineering, or a related technical field (or equivalent experience).
AI & GPU Infrastructure: Hands-on experience with LLM inference pipelines (Ollama, llama.cpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and running local models on consumer-grade hardware.
Agentic Frameworks: Practical experience with modern agentic frameworks (e.g., OpenClaw, LangChain, AutoGPT) and a working understanding of how multi-agent systems plan, act, and use tools.
Systems & OS Knowledge: Strong understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security.
Programming Languages: Proficiency in C++ (performance-critical systems and OS integration), Python (AI and orchestration logic), and TypeScript (agent plugins and tooling).
Communication: Ability to translate complex technical decisions into clear documentation and collaborate effectively across diverse engineering teams.
Ways to stand out from the crowd:
Demonstrated open-source contributions to AI agent platforms or inference/orchestration tools (especially OpenClaw or llama.cpp).
Deep knowledge of NVIDIA GeForce RTX architecture and its specific constraints and advantages for edge AI.
Experience building virtualization, containerization, or sandboxing tools natively for Windows.
Active technical community presence (blogs, talks, whitepapers) at the intersection of AI, security, and local compute.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most talented people on the planet working for us. As part of our team, you will have the opportunity to influence the future with your vision and expertise. Are you creative? Are you driven not just by data or the need to know why, but yearn to ask, 'why not'? We want to hear from you.
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- 12+ years of professional software engineering experience with a track record of shipping performance-critical systems.
- BS, MS, or PhD in Computer Science, Computer Engineering, or related field (or equivalent experience).
- Hands-on experience with LLM inference pipelines (Ollama, llama.cpp, vLLM) and running local models on consumer hardware.
- GPU-accelerated computing experience (CUDA, TensorRT).
- Practical experience with agentic frameworks (OpenClaw, NemoClaw, LangChain, AutoGPT) and multi-agent orchestration.
- Strong understanding of Windows OS internals, process isolation, and sandboxing technologies.
- Proficiency in C++ for performance-critical systems and OS integration.
- Proficiency in Python for AI and orchestration logic.
- Proficiency in TypeScript for agent plugins and tooling.
- Strong communication skills to document and collaborate across teams.
- Open-source contributions to AI agent platforms or inference tools (e.g., OpenClaw, llama.cpp).
- Deep knowledge of NVIDIA GeForce RTX architecture and constraints for edge AI.
- Experience building virtualization, containerization, or sandboxing tools natively for Windows.
- Active technical community presence (blogs, talks, whitepapers) at intersection of AI, security, and local compute.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”







