Data Engineer
TLDR: We’re looking for a Data Engineer who can design and build our data pipelines from scratch – handling petabytes of logs, events, and model traces – and create a clean, reliable environment for production, testing, and research workloads.
About Us
White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale.
- We’ve raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others
- We process over one hundred million API calls every month
- We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model
We’re a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built – you’re the one we need.
What You’ll Do
- Own and evolve our internal data tooling
- Scrape external sources, turn raw chaos into structured datasets, and keep them fresh and reliable
- Build and maintain pipelines to transform and version data, ensuring quality through testing and monitoring
- Create new data products that directly address business needs
- Diagnose and fix pipeline issues before they become someone else’s problem
- Ship analytics and dashboards that people actually use
- Jump into data and infra tasks where needed and make things more robust
What We’re Looking For
- You’re strong in Python and SQL and comfortable working with messy, real-world data
- You have solid experience with web scraping and know how to make pipelines reliable, monitored, and resilient
- You’ve worked with PostgreSQL (or similar) and understand how to structure and query data efficiently