Cloudglue - Video Understanding Infrastructure

Cloudglue is a Y Combinator-backed startup building developer APIs that turn video and audio into structured, searchable data. Think of us as the Stripe for video understanding - we handle the hard infrastructure (transcription, visual analysis, search, extraction) so developers can build on top of video without managing ML pipelines themselves.

We process millions of minutes of video for customers building search, analytics, and automation products. The engineering problems are real: high-throughput media processing, complex search and retrieval over multimodal data, and APIs that need to be fast, reliable, and a pleasure to use.

Our team has shipped large-scale systems at Snapchat and Amazon, with work presented at AWS re:Invent, KubeCon, NeurIPS, and DEF CON. We’re a small, technical team where engineers have real ownership and direct impact on the product.

The Role

We’re looking for a founding full stack engineer to build and ship features across Cloudglue’s APIs, developer dashboard, SDKs, and documentation. You’ll be one of the first engineers on the team - this is a high-ownership role where you’ll shape the product and the engineering culture.

You’ll work across the entire stack, from React frontends to backend services to database queries. Day to day, you’ll:

• Own features end-to-end - from API design to UI to production deployment
• Work directly with founders on core product decisions
• Build the tools and interfaces developers use to work with large video collections
• Ship quickly and iterate based on real customer feedback

If you like building polished developer products and moving fast across frontend, backend, and infrastructure, this role is for you.

What You’ll Do

• Build across the stack: Design and ship features spanning frontend (React/TypeScript), backend services (Node.js/Python/Go), and databases (Postgres).
• Developer tools: Build and maintain REST APIs, SDKs (Python/JS), the developer dashboard, and interactive playgrounds.
• Product integration: Wire up ML pipeline outputs (transcription, visual analysis, search results) into usable product surfaces and API responses.
• Ownership: Take features from idea through implementation, deployment, monitoring, and iteration.
• Collaborate: Work directly with founders, infrastructure engineers, and customers. Short feedback loops, no layers of process.