Autonomous Agent Engineer

at Nvidia

USD 184,000-356,500 per year

MIDDLE SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 3 Agentic AI @ 3 Audit @ 3 Distributed Systems @ 6 Go @ 3 Kubernetes @ 3 LLM @ 3 Linux @ 3 Observability @ 3 Python @ 3 Rust @ 5 Security @ 3

Details

We are building the infrastructure that lets AI agents operate autonomously and securely. 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.

Responsibilities

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.

Requirements

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 an 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.

Compensation & Benefits

Base salary ranges provided by level:
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
Eligible for equity and benefits (link to company benefits referenced in posting).

Other details

Applications accepted at least until April 13, 2026.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.