Senior Engineer - AI Agents and Systems

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.

• Local inference optimization: optimize performance of local LLMs 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 (Nemo Claw, Open Claw) to run natively and reliably on Windows; implement orchestration logic for multi‑agent planning and tool usage on constrained consumer hardware.
• Sandboxing & security: implement policy‑based privacy and security frameworks for autonomous agents, handling file system access, secure inference routing, and network egress within 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 Open Claw 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.

• 12+ years of professional software engineering experience, with a track record of shipping performance‑critical systems.
• BSc, MSc, or PhD in Computer Science, Computer Engineering, or related technical field (or equivalent experience).
• Hands‑on experience with LLM inference pipelines (Ollama, llama.cpp, vLLM), GPU‑accelerated computing (CUDA, TensorRT), and running local models on consumer‑grade hardware.
• Practical experience with modern agentic frameworks (e.g., Open Claw, Lang Chain, AutoGPT) and a working understanding of how multi‑agent systems plan, act, and use tools.
• Strong understanding of Windows OS internals, process isolation, sandboxing technologies, and system‑level security.
• Proficiency in C++, Python, and Type Script.
• Ability to translate complex technical decisions into clear documentation and collaborate effectively across diverse engineering teams.

• Demonstrated open‑source contributions to AI agent platforms or inference/orchestration tools (especially Open Claw 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.

Base salary will be determined based on location, experience, and the pay of employees in similar positions. For Level 5 the range is $224,000‑$356,500, and for Level 6 it is $272,000‑$431,250. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. We do not discriminate 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.