turbopuffer is looking for product engineers who want to advance the frontier of search. we're doubling down on our developer experience this year and looking to ship a host of highly requested features and improvements (playgrounds, observability, alerting, insights, billing).
what you'll do:
design and implement end-to-end improvements to our overall developer experience from the UX (dashboard, docs, site, SDKs) to our core database.
help customers understand, monitor, and optimize their tpuf workloads.
write crisp docs
must have:
product engineering
you've worked extensively with browser technologies (HTML/CSS/JS/TS) and web apps in general (databases, APIs)
you are passionate about UX and can think like a product manager
you are driven by solving user problems
you have an eye for design
domain expertise
you’ve maintained and iterated on web-based products at scale
you have prior experience with multi-tenant SaaS apps (billing, authentication, authorization)
typist — you can write well and explain complex ideas simply
human — you build trust and admit what you don’t know
nice to have:
experience in the React ecosystem (shadcn/ui, Next.js, Tailwind, Vercel) and/or backend frameworks (Rails, Phoenix, Django)
an interest in vector and full-text search and experience interacting with tools in the space
prior experience with Rust
tpuf is hardcore & whimsical. we value:
overstep > understep
show > tell
complexity is earned
showing up as part of our customer’s team
making stuff easy to react to
Skills Required
- Extensive experience with browser technologies and web applications
- Passionate about UX and problem-solving
- Experience with multi-tenant SaaS applications
- Ability to write clearly and explain complex ideas
What We Do
turbopuffer is a serverless search engine that combines vector and full-text search using object storage. It is designed to make large amounts of data searchable for AI applications, offering high scalability, performance, and cost-efficiency by separating compute and storage. It serves as a critical infrastructure layer for companies needing to retrieve context for AI models, handling billions of documents with low latency.
