About LanceDB
LanceDB is a high-performance, open-source, cloud-native database built for multimodal workflows. From vector search at multi-billion scale to real-time retrieval, feature engineering, and analytics across large-scale datasets, LanceDB powers AI data infrastructure.
We’re looking for a hands-on, technically strong Support Engineer who will be the bridge between our engineering team and enterprise users of LanceDB, helping our customers debug distributed databases built in Rust.

Your Role

• As one of the early team members, build our support infrastructure and practices while handling customer cases:

  • Develop and maintain knowledge-base articles, runbooks, and support tooling that document common issues, best practices, deployment patterns, and performance tuning.

  • Contribute to metrics around support response-times, resolution times, customer satisfaction, and help build a scalable support organization as we grow.

  • Work proactively: identify recurring issues, escalate product bugs or UX gaps, propose improvements in the support process, and advocate for the customer in the roadmap.

• Serve as one of the primary technical points of contact for our customers: troubleshoot issues, respond to escalations, and guide customers through full lifecycle support for large-scale deployments of LanceDB.

• Work in close collaboration with our engineering and product teams to reproduce issues, debug root causes, propose remediation, and drive fixes or enhancements.

• Dive deeply into distributed database internals: query execution, storage engine, indexing, sharding, replication, fail-over, and cloud orchestration (Kubernetes, serverless-style deployments).

• Use and contribute to Rust codebases: reproduce customer environments, inspect logs, build diagnostic tools, run instrumentation, apply patches and configuration changes.

What We’re Looking For
Must-have (please do not apply unless you meet all of the criteria in this section)

• 8+ years of professional experience in a support / operations / troubleshooting role in a distributed database or data infrastructure environment.

• Demonstrated experience with distributed database systems, cloud-native data platforms (AWS, GCP, or Azure), and Kubernetes or serverless deployment models.

  • Strong knowledge of distributed systems concepts: sharding, replication, consensus, failure modes, resource contention, performance bottlenecks, and cloud-native orchestration (Kubernetes, containerization, autoscaling).

• Demonstrated experience with at least one of the following: vector/feature stores, analytics engines or big data systems.

• Very comfortable with reading logs and correlating them with source code, working with Grafana dashboards, and creating shell scripts or Python code to assist in debugging.

• Excellent customer-facing communication skills: you’ll be working directly with high-value customers, so you must be comfortable explaining complex technical issues clearly, managing expectations, and advocating for the customer.

• Strong sense of ownership, urgency, correct prioritization under pressure, and ability to work closely with engineering teams to drive resolution.

• Comfortable working in a fast-moving startup environment with high autonomy and evolving responsibilities.

Nice-to-have

• Proficiency in Rust: you should be comfortable reading, navigating, and debugging code; ideally you’ve built or debugged production-quality systems written in Rust.

• Familiarity with storage engine internals, indexing/data layout, performance tuning, and profiling tools.

• Contributions to open-source projects (especially Rust), or experience writing diagnostic tools, debuggers, or instrumentation.

• Experience deploying and monitoring systems in large-scale production environments: logging/observability (e.g., Prometheus, Grafana, OpenTelemetry), alerting, SLOs/SLAs.

• Previous experience creating new runbooks, selecting and configuring support ticketing systems, and defining incident response processes.

Why Join Us

You’ll join a world-class team of open-source builders (co-authors of pandas, and contributors to HDFS, Arrow, Iceberg, and HBase) working on cutting-edge AI infrastructure. You’ll work together on building systems that support next-generation AI workloads, while helping define how LanceDB runs and scales in production infrastructure at some of the most innovative companies of our time.