Kubernetes · Docker · Python · Java · AWS
ABOUT THE ROLE
Join a small AI and machine learning product team building infrastructure for user-facing products and services. You will own core infrastructure work end to end, helping the team ship reliable systems that support growing products and demanding workloads.
WHAT YOU'LL DO
- Build and operate cloud infrastructure and containerized services for production workloads.
- Design durable workflows for long-running tasks and infrastructure supporting AI agents or machine learning workloads.
- Develop and improve platform capabilities across data storage, service reliability, and product infrastructure.
- Lead work from requirements and architecture through implementation, launch, and ongoing iteration.
- Collaborate closely with a small team to deliver practical solutions quickly and communicate tradeoffs clearly.
WHAT WE'RE LOOKING FOR
- Two to ten years of experience in infrastructure, platform, or backend engineering, with scope and responsibility that have progressed over time.
- Production experience managing infrastructure as code with CDK or Terraform and operating Docker-based services.
- Hands-on experience with Temporal or a comparable durable workflow orchestrator.
- Experience running production cloud infrastructure on AWS, GCP, or Azure at significant scale, or strong evidence of working with large data volumes.
- Deep production database experience, including schema design, scaling, and performance tuning; the current stack includes Postgres, Redis, and ClickHouse.
- Experience at a startup or a combination of large-company and