We're building a storage layer specifically designed for AI observability and evaluation. We're a fast-moving team looking for a systems / database engineer to help design, optimize, and harden our system. Within 6 months, we've gone from idea to production system but there is still lots to build and optimize. You'll be working on execution, storage layout, performance profiling, and scaling to trillions of traces. This role is based in San Francisco.
Engineer performant Rust code for ingestion and query execution
Optimize for cost and speed, heavily utilizing memory and CPU profiling
Integrate tightly with cloud object stores (S3/GCS/Azure Blob)
Deploy our distributed database services on Kubernetes (multi-tenant, high throughput, low latency)
Contribute to observability for the storage engine itself (metrics, tracing, debug tooling)
5+ years in systems/database engineering with strong experience in a systems programming language (Rust, C++). Rust strongly preferred, as it is the language we use.
Knowledge of database internals is a plus: query engines, storage systems, indexing, and compaction
Proficiency in systems performance analysis: memory allocation, CPU hotspots, lock contention, async runtimes.
Familiarity with similar query execution engines is a plus
Experience with Kubernetes, distributed systems, and cloud object storage is a plus.
Strong fundamentals in networking, OS concepts, and systems debugging.
Salary Range: $175,000-$240,000 USD
Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.