Senior Engineer - AI Agents and Systems

What You Will Be Doing

• Act as the lead engineer for developing the agent frameworks natively on Windows environments.
• Shape the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
• Lead the engineering efforts to optimize the agent runtimes for Windows.
• Ensure that autonomous agents operate within thorough, policy-based privacy and security frameworks (e.g., handling filesystem access, secure inference routing, and network egress).
• 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.
• Foster a collaborative engineering culture by mentoring other engineers, establishing best practices for AI agent deployment, and writing reliable, production-ready code.

What We Need To See

• 10+ years of relevant professional software engineering experience, with at least 3+ years in 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 (Ollama, Llamacpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware.
• Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, Hermes, LangChain) and an understanding of how multi-agent systems plan, act, and use tools.
• Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration) and Python (for AI/blueprint logic).
• Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.

Pay

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

Schedule

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.

Benefits

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.

About the Role

We are looking for a Senior Engineer to serve as a key technical leader in deploying advanced AI agent frameworks and local runtimes to Windows and NVIDIA GeForce RTX GPUs.

Responsibilities

• Act as the lead engineer for developing the agent frameworks natively on Windows environments.
• Shape the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
• Lead the engineering efforts to optimize the agent runtimes for Windows.
• Ensure that autonomous agents operate within thorough, policy-based privacy and security frameworks (e.g., handling filesystem access, secure inference routing, and network egress).
• 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.
• Foster a collaborative engineering culture by mentoring other engineers, establishing best practices for AI agent deployment, and writing reliable, production-ready code.

Requirements

• 10+ years of relevant professional software engineering experience, with at least 3+ years in 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 (Ollama, Llamacpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware.
• Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, Hermes, LangChain) and an understanding of how multi-agent systems plan, act, and use tools.
• Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration) and Python (for AI/blueprint logic).
• Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.

Qualifications

• Deep understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security architecture.
• Proven understanding of LLM inference pipelines (Ollama, Llamacpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware.
• Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, Hermes, LangChain) and an understanding of how multi-agent systems plan, act, and use tools.
• Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration) and Python (for AI/blueprint logic).
• Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.

Skills

• Deep understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security architecture.
• Proven understanding of LLM inference pipelines (Ollama, Llamacpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware.
• Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, Hermes, LangChain) and an understanding of how multi-agent systems plan, act, and use tools.
• Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration) and Python (for AI/blueprint logic).
• Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.

Benefits

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.

Pay

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

Schedule

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.

Application Instructions

Applications for this job will be accepted at least until May 15, 2026.