About the Role

Join an AI product team building the platform that supports customer-facing agent applications. You will work across backend infrastructure, developer tooling, and MLOps to help research and product teams develop, deploy, and operate reliable systems.

What You'll Do

Build and maintain cloud infrastructure for compute, storage, CI/CD, observability, and security.

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

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

Improve build, test, and release workflows from research prototypes through production.

Monitor service and pipeline performance, diagnose bottlenecks, and improve reliability and reproducibility.

Design backend services for agent hosting, availability, tracking, security, networking, and scaling.

Contribute to platform architecture and infrastructure strategy as the product grows.

What We're Looking For

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

Experience building a backend platform from scratch for an external product, ideally involving LLMs or agents.

Recent hands-on experience with production LLM or agent systems, such as serving, orchestration, tool use, memory, or evaluation.

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.

Experience spanning both larger technology organizations and startups or research environments, with broad ownership of a system.

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

Compensation & Benefits

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

Location

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