Senior Engineer - AI Agents and Systems

at Nvidia
USD 184,000-356,500 per year
SENIOR
✅ On-site

Used Tools & Technologies

Not specified

Required Skills & Competences

Security @ 4 Python @ 6 Leadership @ 4 Technical Leadership @ 4 LLM @ 4 CUDA @ 4 GPU @ 4 AI @ 4 vLLM @ 4 TensorRT @ 4 LangChain @ 4

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 is a senior technical leadership position focused on deploying advanced AI agent frameworks and local runtimes to Windows and NVIDIA GeForce RTX GPUs, enabling open-source AI agents (e.g., Nemoclaw, OpenClaw) to run locally, safely, and efficiently on consumer PCs.

Responsibilities

  • Lead development of agent frameworks natively on Windows, shaping the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
  • Optimize agent runtimes for Windows to ensure autonomous agents operate within policy-based privacy and security frameworks (filesystem access controls, secure inference routing, network egress controls).
  • Partner 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.
  • Ensure integration of powerful local inference (Nemotron models) with privacy routers and sandboxed execution to help create a desktop AI operating system foundation.

Requirements

  • 10+ years of relevant professional software engineering experience, with 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 and practical experience with LLM inference pipelines (examples given: Ollama, Llamacpp, vLLM) and running local models on consumer-grade hardware.
  • Experience with GPU-accelerated computing (CUDA, TensorRT) and optimizing inference on NVIDIA GPUs (GeForce RTX).
  • Practical experience with modern AI orchestration and agentic frameworks (examples: OpenClaw, Hermes, LangChain) and knowledge of multi-agent system behaviors (planning, acting, tool use).
  • 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

  • Competitive base salary with ranges specified by level.
  • Eligibility for equity and benefits; a generous benefits package is mentioned.

Compensation (as listed)

  • Base salary range for Level 4: 184,000 USD - 287,500 USD
  • Base salary range for Level 5: 224,000 USD - 356,500 USD

Additional details

  • Applications accepted at least until May 15, 2026. This posting is for an existing vacancy.
  • NVIDIA uses AI tools in its recruiting processes and states commitment to diversity and equal opportunity employment.