Deliver production-ready software at AI speed. CircleCI helps modern teams validate, test, and ship every change with intelligent automation. Backed by 500 Global, IVP and Sapphire.
About the role
You don't just patch problems, you ask why they happened. You'll fix the immediate issue, then solve the underlying team practice, process, or system that let it through. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Build AI-natively. AI is how we work. It's not a productivity layer on top of engineering, but the default starting point for how problems get approached and solved
- Shape how we store data at scale. Own and harden our ClickHouse-based storage layer. Design schemas for known and emerging access patterns, and tune ingestion and query performance to support production-scale data
- Champion observability. Use Honeycomb, Datadog, and Rollbar to understand ingestion lag, query latency, and data correctness. For a data platform, operational data drives stability, not just incident response
- Keep things moving. You take ambiguous data problems from design to production quickly, and you help the people around you move faster too
More about this role
CI/CD has been solved. Now it's being reinvented. AI agents don't just run pipelines. They write code, trigger builds, interpret failures, and propose fixes. The interfaces that developers use to understand and trust that work don't exist yet. We're building them.
At CircleCI, our guiding principles aren't posters on a wall. We learn fast: we run experiments, accept failure, and scale what works. We think like the customer: every decision connects back to the developer sitting in front of a failing build at 2 am. We own the outcome: not just our slice of it, but the whole thing. If that's how you already work, you'll fit here.
Every pipeline, job, and test that runs on CircleCI generates data, and that history is one of our biggest advantages in an agentic software delivery lifecycle. Flaky test detection, test insights, pipeline search, and agents that reason about why a build failed all depend on fast, reliable access to it.
The Query team owns the system that makes this possible. We pull product data out of the transactional services that create it and store it in datastores built for historical and analytical workloads. We serve it through domain-level APIs to CircleCI's...
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