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LanceDB is an AI-native Multimodal Lakehouse that enables researchers to curate and manage petabytes of video, audio, and derived signals with minimal code. Customers including Runway, Midjourney, and Netflix use LanceDB to build frontier models, world models, robots, and autonomous vehicles.
As Senior System Test Engineer, you will own the correctness, reliability, and performance of Lance and LanceDB under demanding production conditions. This is a hands-on role at the intersection of distributed databases, systems engineering, and test infrastructure.
Key responsibilities:
- Define and drive system-level testing across correctness, reliability, scalability, and performance, prioritizing highest-risk platform behaviors
- Build automated test frameworks and realistic workloads covering ingestion, concurrent reads/writes, indexing, querying, and dataset maintenance
- Validate data integrity and consistency guarantees under concurrency, retries, partial failures, and recovery scenarios
- Develop fault-injection and resilience tests for process crashes, network disruptions, storage errors, resource exhaustion, and interrupted operations
- Design load, stress, and long-running soak tests; identify regressions in latency, throughput, resource usage, and search quality
- Test upgrades, compatibility, and recovery scenarios to ensure predictable platform behavior 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
- Develop and continuously improve reproducible test environments, integrating reliable checks into CI and release workflows
- Use AI coding assistants and tools to develop test harnesses, explore failure scenarios, analyze results, and accelerate debugging
Requirements:
- 10+ years of software engineering, system test engineering, or test infrastructure experience, with substantial experience building or validating distributed databases or large-scale data systems
- Deep understanding of distributed databases: consistency models, replication, partitioning, concurrency control, durability, and failure recovery
- Proven track record designing tests that verify system invariants and uncover data corruption, race conditions, and failures under load or partial outages
- Strong programming skills in Python and at least one systems language (Rust, C++, Java, or Go); ability to build maintainable test infrastructure and debug product code
- Hands-on experience with fault injection, performance testing, workload generation, and automated testing in distributed environments
- Demonstrated ability to use AI tooling adeptly in daily engineering work, including coding assistants and agent-based workflows, with sound judgment validating outputs
- Experience with Linux, cloud infrastructure, containers, CI/CD, and observability tools
- Ability to own ambiguous projects, prioritize risk, communicate findings clearly, and collaborate closely with engineers
Nice to have:
- Experience testing database storage engines, query engines, vector search, or cloud object storage integrations
- Familiarity with LanceDB, Lance, Apache Arrow, DataFusion, Parquet, or related data infrastructure
- Experience with property-based testing, fuzzing, differential testing, or distributed consistency testing
- Experience with Kubernetes, infrastructure as code, and large-scale test environment orchestration
- Contributions to open-source databases, distributed systems, or testing frameworks
