About the Role
Join a small engineering team at an AI and machine learning startup to build and operate reliable infrastructure for user-facing products and AI workloads. You will own core platform systems and help the team ship quickly as its products and usage grow.
What You'll Do
Build and operate cloud infrastructure and containerized services for production products.
Design durable workflows and systems that support AI agents, long-running jobs, model routing, and inference workloads.
Own infrastructure projects from requirements and architecture through launch and ongoing improvement.
Design, scale, and tune databases, including systems using Postgres, Redis, and ClickHouse.
Work with product engineers to deliver dependable platform capabilities and respond to changing product needs.
What We're Looking For
Two to ten years of experience in infrastructure, platform, or backend engineering, with demonstrated progression into staff, lead, or equivalent scope.
Production experience managing cloud infrastructure on AWS, GCP, or Azure, using infrastructure as code such as CDK or Terraform, and running Dockerized services.
Hands-on experience with Temporal or a comparable durable workflow orchestration system.
Experience operating cloud systems at substantial scale, supporting hundreds of thousands of users, or working with large volumes of data.
Strong production database skills, including schema design, scaling, and performance tuning.
Experience at a startup or a combination of large-company and startup experience; familiarity with TypeScript and React is useful.
Regular use of AI coding tools and the ability to describe your development workflow; experience building infrastructure for AI agents or machine learning workloads is a plus.
Compensation & Benefits
Base salary is $200,000 to $300,000 USD annually. Visa sponsorship is available. Equity details were not provided.
Location
On-site in San Francisco, United States.