Role at a glance
- Salary
- $184K – $356.5K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ years building distributed systems, infrastructure, or developer platforms at scale
- Education
- BS or MS in Computer Science, Engineering, or related field (or equivalent experience)
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Role Summary
This role builds infrastructure for autonomous AI agents at NVIDIA, including execution environments, state management systems, security boundaries, SDKs, CLIs, and developer tooling. The team creates a unified experience for securely running agent workloads across sandboxed compute environments and supports reliable, observable, and auditable operations.
What You'll Do
- Architect sandboxed compute environments for agents to execute code, access tools, and interact with external services.
- Design and ship Python and Go SDKs and CLI tooling for provisioning and managing isolated agent workloads.
- Create onboarding templates, reference implementations, and CLI workflows for secure execution.
- Build state management for long-running agent operations, including checkpoint and recovery.
- Embed isolation policies, secrets injection, network policies, capability declarations, and kill switches into SDK primitives.
- Engineer workload identity and delegated tool access integrations, plus observability and audit infrastructure including structured...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
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 in containers, microVMs, Kubernetes, and Linux security primitives; track record of shipping developer SDKs or CLIs adopted by multiple teams; experience building agents using various frameworks and harnesses in enterprise context; proficiency in Python, Go, Rust, or similar.
Required
- 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
Preferred
- 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
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 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 the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.