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Autonomous Agent Engineer

US, CA, Santa Clara
Full Time On-site

Summary

Job Description

We're building the infrastructure that lets AI agents operate autonomously and securely at NVIDIA. This role owns the execution environments, state management systems, and security boundaries that make autonomous agents safe and reliable. The team designs and ships SDKs, CLIs, and developer tooling that turn complex sandboxing into a straightforward experience for agent builders and users across the company.

Today "sandbox" means different things to different teams: Docker containers, microVMs, or full virtual machines, each with different security guarantees. We need someone who can navigate these tradeoffs and build a unified developer experience on top of them. This work is greenfield! Many of the problems we're solving don't have existing industry solutions, and we want someone who is energized by that.

What you'll be doing:

The day-to-day is designing and building infrastructure that other engineers depend on:

  • Architect sandboxed compute environments where agents securely execute code, access tools, and interact with external services

  • Design and ship SDKs (Python, Go) and CLI tooling for provisioning and managing agent workloads in isolated environments

  • Create onboarding templates, reference implementations, and CLI workflows that make secure execution the default

  • Build state management for long-running agent operations, including checkpoint and recovery

  • Embed security into SDK primitives like isolation policies, secrets injection, network policies, capability declarations, and kill switches

  • Engineer auth integrations for workload identity, delegated tool access, and scope attenuation without static secrets

  • Build observability and audit infrastructure: structured logs, decision traces, security telemetry, and audit trails wired into enterprise monitoring

What we need to see:

  • BS or MS in Computer Science, Engineering, or related field (or equivalent experience)

  • 8+ years building distributed systems, infrastructure, or developer platforms at scale

  • Deep systems engineering skills: containers, microVMs, Kubernetes, Linux security primitives

  • Track record of shipping developer SDKs or CLIs that are adopted by multiple teams

  • Experience building agents using various frameworks and harnesses in enterprise context

  • Proficiency in Python, Go, Rust, or similar

Ways to stand out from the crowd:

  • Experience building execution environments for agentic AI systems or LLM applications that execute code autonomously

  • Experience with sandboxing and isolation technologies (gVisor, Firecracker, Kata Containers, V8 isolates, or similar)

  • Strong security fundamentals: threat modeling, auth, least privilege, secrets management

  • Designed multi-tenant execution platforms, serverless infrastructure, or sandboxed compute at scale

  • Background in durable execution patterns or checkpoint/recovery systems for long-running workloads

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.

Applications for this job will be accepted at least until April 13, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

About Nvidia

Nvidia

NVIDIA is one of the most influential technology companies in the world, powering the modern era of artificial intelligence, high-performance computing, graphics, and autonomous systems. Originally known for its leadership in gaming GPUs, NVIDIA has evolved into the backbone of AI infrastructure, designing the chips, software, and systems that train and deploy large-scale AI models used across industries from healthcare and robotics to autonomous vehicles and scientific computing.

For job seekers, NVIDIA offers opportunities at the forefront of deep tech, spanning software engineering, AI research, systems engineering, hardware design, networking, robotics, and developer tools. A major focus of its work is the CUDA software platform and AI ecosystem, which enables developers to program GPUs at massive scale and has become foundational to modern machine learning and data center computing. This makes NVIDIA especially attractive to engineers, researchers, and technologists who want to work directly on the infrastructure powering today’s AI revolution.

Unlike traditional hardware companies, NVIDIA operates as a full-stack computing platform company, integrating silicon, systems, and software into a unified ecosystem. Employees may work on everything from GPU architecture and data center systems to AI frameworks, simulation platforms like Omniverse, and autonomous vehicle technology through the DRIVE platform. This breadth allows teams to operate at the intersection of research and production-scale deployment, with direct impact on global computing infrastructure.

As demand for AI, accelerated computing, and autonomous systems continues to grow rapidly, NVIDIA remains one of the most important employers in technology and advanced engineering. For professionals seeking a high-impact career at the center of AI development—where breakthroughs quickly translate into real-world systems at global scale—NVIDIA stands out as one of the most dynamic and sought-after destinations in the industry.

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