The multimodal lakehouse for AI, accelerating large-scale data curation and feature engineering so teams can build better models faster. Backed by Y Combinator and CRV.
About the role
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. As one of the early team members, build our support infrastructure and practices while handling customer cases:
What they're looking for
- 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
More about this role
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.
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.
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,...
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