AI Infrastructure Engineer
Engineering · Full-time · San Francisco / Remote
Apply ↓Build the infrastructure that makes private, rights-clean data usable for AI companies with reliable ingestion, processing, access control, and delivery.
Sphere sits between data owners and AI buyers, which means our infrastructure has to handle trust, scale, permissions, and performance from the beginning.
You will work on systems for data ingestion, file processing, metadata extraction, secure delivery, auditability, and the backend services that power marketplace transactions.
What you'll do
- Design backend services for secure data ingestion, processing, storage, indexing, and delivery.
- Improve reliability, observability, and performance across APIs, queues, workers, databases, and cloud services.
- Build permissioning and audit systems that support enterprise-grade data licensing workflows.
- Collaborate with product and GTM teams to turn buyer requirements into robust technical capabilities.
You may be a fit if
- You have built production backend systems in cloud environments and understand reliability tradeoffs.
- You are comfortable with TypeScript, Node.js, databases, object storage, background jobs, and API design.
- You think carefully about security, privacy, data integrity, and operational visibility.
- You want to work on the infrastructure layer behind AI data rights, licensing, and monetization.