About the Role

Build the infrastructure and developer tools that support an AI product, from research and experimentation through reliable customer-facing deployments. This platform role works closely with product and research teams to make agent systems robust, scalable, and efficient.

What You'll Do

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

Build internal developer tools, automation, and shared libraries that help teams work efficiently.

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

Improve build, test, and release workflows to support moving prototypes into production.

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

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

What We're Looking For

Five to twelve years of backend or platform engineering experience, with senior or staff-level individual contributor scope and a hands-on coding practice.

Experience building a backend platform from the ground up for a customer-facing product, ideally involving LLM or agent workloads.

Recent experience operating production infrastructure for LLM or agent applications, including 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 across both larger technology organizations and early-stage startup or research environments.

Familiarity with data pipelines, job scheduling, or machine learning experimentation workflows.

Compensation & Benefits

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

Location

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