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Senior System Test Engineer

LanceDB· Engineering
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United States | Canada$180k - $250kFull-timePosted 1w ago

About the role

Senior System Test Engineer responsible for driving correctness, reliability, and performance of Lance and LanceDB under production conditions, building test frameworks and workloads, and partnering with engineering to turn architectural risks and real customer workloads into automated, reproducible tests.

Responsibilities

  • 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.
  • Collaboration and debugging: 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.
  • Environment/tooling: Develop and continuously improve reproducible test environments, integrating reliable, actionable checks into CI and release workflows.
  • AI tooling: Use AI coding assistants and other AI tools to develop test harnesses, explore failure scenarios, analyze results, and accelerate debugging, independently verifying generated code and conclusions.

Qualifications

  • 10+ years of experience in software engineering, system test engineering, or test infrastructure, with substantial experience building or validating distributed databases or large-scale data systems
  • Deep understanding of distributed databases, including consistency models, replication, partitioning, concurrency control, durability, and failure recovery
  • Proven track record of designing tests that verify system invariants and uncover data corruption, race conditions, and failures that emerge only under load or partial outages
  • Strong programming skills in Python and at least one systems language such as Rust, C++, Java, or Go, with the 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 about 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 to drive issues to resolution

Skills

Required:System test strategyTest frameworks and workloadsData integrity and fault injectionPerformance testingUpgrades and compatibility testingLinux / cloud / CI/CD / observability
Nice to have:AI tooling for testing

Benefits

  • Medical, dental, vision, and life insurance
  • 401(k) retirement plan
  • Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA)
  • Commuter benefits
  • Generous paid time off
  • Paid parental leave program for birthing, non-birthing, adoptive, and foster parents
Last updated Oct 14, 2026. Interested? Apply on the company site.
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About LanceDB

Designed for Multimodal. Built for Scale.

LanceDB is the first open-source AI-Native Multimodal Lakehouse.

Vector DatabaseMultimodal dataAI workloadsData infrastructureHybrid searchModel trainingStorageSearch
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