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About LanceDB

AI advances at the speed of its research, and research moves at the speed of its data. LanceDB is the AI-native Multimodal Lakehouse: one system where a researcher curates petabytes of video, audio, and every signal derived from them with a few lines of Python, and the next training run starts as fast as the next idea. Customers like Runway, Midjourney, and Netflix build the future of AI on LanceDB, from frontier and world models to robots and autonomous vehicles.

About the Role

As the Senior System Test Engineer at LanceDB, you will drive the correctness, reliability, and performance of Lance and LanceDB under demanding production conditions. You'll work at the intersection of distributed databases, systems engineering, and test infrastructure, building the frameworks and workloads that expose failures before our users encounter them.

You'll partner closely with engineering to turn architectural risks and real customer workloads into automated, reproducible tests, and to diagnose and fix complex failures. This is a hands-on role with ownership of system-level test strategy and execution, where you'll use AI tooling adeptly to accelerate development and investigation while maintaining rigorous validation.

This is an opportunity to define the quality bar for infrastructure powering the next generation of AI workloads, and to directly influence product architecture, release confidence, and the reliability our users depend on as they move from experimentation to production at scale.

What You'll Do

• System test strategy: Define and drive system-level testing across correctness, reliability, scalability, and performance, prioritizing the highest-risk behaviors in the platform.
• Test frameworks and workloads: Build automated test frameworks and realistic workloads covering ingestion, concurrent reads and writes, indexing, querying, and dataset maintenance.
• Data integrity and fault injection: Validate data integrity and documented consistency guarantees under concurrency, retries, partial failures, and recovery. Develop fault-injection and resilience tests for process crashes, network disruptions, storage errors, resource exhaustion, and interrupted operations.
• Performance testing: Design load, stress, and long-running soak tests, and identify regressions in latency, throughput, resource usage, and search quality.
• Upgrades and compatibility: Test upgrades, compatibility, and recovery scenarios to ensure the platform behaves predictably as software and workloads evolve.
• Partner closely with engineers to investigate failures using logs, metrics, traces, and source code, reduce complex issues to minimal reproductions, and drive fixes and regression coverage.