About the Role

Join an AI product team building the platform and backend systems that support agent applications. You will work across infrastructure, developer tooling, and MLOps to help research and product teams move reliably from experimentation to production.

What You'll Do

Build and maintain cloud infrastructure, storage, CI/CD pipelines, observability, and security for research and product environments.

Develop internal developer tools, automation, and shared libraries that improve team productivity.

Create reliable systems for data management, model experimentation, evaluation, and deployment.

Design build, test, and release workflows that connect prototypes to production services.

Monitor service and pipeline performance, troubleshoot bottlenecks, and improve reproducibility.

Contribute to platform architecture and scaling strategy in collaboration with research and product teams.

What We're Looking For

5 to 12 years of backend or platform engineering experience, including senior or staff-level individual-contributor work and daily coding.

Experience building a customer-facing product platform from the ground up, ideally for LLM or agent applications, and operating production LLM or agent infrastructure recently.

Strong backend fundamentals in Python or Go, APIs, databases and storage, and distributed systems.

Working experience with Kubernetes and a major cloud provider such as AWS or Google Cloud, plus tools such as Postgres, object storage, or vector stores.

A blend of experience in larger technology organizations and early-stage startup or research environments, with ownership of a complete system.

Familiarity with data pipelines, job scheduling, or ML experimentation workflows.

Compensation & Benefits

Base salary: $200,000 to $300,000 annually. Visa sponsorship is available.

Location

On-site in Palo Alto, California, United States.