Backend Engineer (TypeScript)

About this role

Who We Are: We build infrastructure that delivers massive amounts of web data to the companies training the world’s most powerful AI models. We're the team that helps to power and support Grass, a bandwidth-sharing network that lets us operate a massive distributed crawler, giving us unique access to high-quality public web data at global scale. On top of that, we’ve built pipelines for ingesting, segmenting, and annotating billions of videos, transcripts, and audio files, powering dataset creation for frontier labs.

We’re lean, technical, and move fast. No red tape, no slow decision-making; just a team of builders pushing to expand what’s possible for open web data and AI. The Role: We are seeking a hands-on Backend Engineer to join a small, dynamic engineering team and help build, improve, and operate the backend services and production tooling that support reliable web data acquisition at scale. This role is ideal for someone who enjoys coding, cares about the quality of what they ship, and can work with a high degree of independence.

You should be comfortable taking a high-level objective, figuring out what needs to be done, and driving it through to a reliable production result without requiring close supervision. Please note: This role requires a work schedule that sufficiently overlaps with EST business hours to collaborate effectively with the team. Who You Are: - Acts with integrity and seeks out responsibility - Demonstrates resilience, resourcefulness, and motivation for getting things done - Organized and process-driven - Approaches challenges as opportunities - Curious and challenges personal assumptions regularly - Welcomes feedback and open dialogue - Values team success over personal recognition What You'll Be Doing: - Build and improve backend code primarily in TypeScript.

- Set up and maintain metrics dashboards for production systems. - Update existing code to support new metrics and improve system observability. - Set up alerts and work closely with DevOps to optimize production systems. - Automate deployments and operational reporting to Slack. - Test systems in production, identify and troubleshoot issues, and fix bugs. - Help clean up and improve the existing codebase. - Write and maintain automated tests.