The opportunity
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences…
What you'll do
Database Performance & Reliability: Dig into the internals of a large-scale, multi-tenant, distributed database — storage, query execution, consensus, change data capture, and shard routing and management. You'll root-cause hard performance, reliability, and stability issues, and partner directly with our open-source database vendor to land fixes upstream.
Database Quality & Automation: Build the testing and quality infrastructure that lets us move fast with confidence on an open-source database. You'll bring tools like Jepsen and other database benchmarks into Airbnb's in-house testing stack, drive CI integration with OSS test suites, and design creative solutions for database tiering and representative load shadowing. As AI accelerates development speed and our availability bar climbs toward 99.99%, this role becomes only more critical to how fast and safely we can ship.
Build the frameworks and tooling around monitoring, observability,: permissions, and service discovery integration.
Dig into the query and storage layers to explain latency differences between: B-tree and LSM-based storage engines.
Design and implement traffic prioritization at the storage layer for: connection pooling, CPU prioritization, and reason about traffic
Test, validate and safely roll out a new CDC architecture while guaranteeing: full transactional correctness across shards.
What they're looking for
- + years building and operating large-scale, Tier 0 distributed systems.
- Hands-on experience with database or storage internals: query execution, storage engines, replication, consensus and testing.
- Ability to own and dive deeply into a complex codebase, ideally an open-source one.
- Experience developing code, maintaining, analyzing, and debugging: high-severity production incidents, leveraging AI agents.
