Role
Engineer focusing on providing optimal user and agent experiences on the LanceDB platform.Takes high-level direction (e.g., "identify where UX is significant ahead of AX and drive more parity") and drives to resultsSuccess looks like a LanceDB platform that incorporates compelling user and agent experiences for exploring and managing their multimodal data, enabling more adoption and increased usage.
Day-to-day
Work with the rest of engineering to optimize user and agent experience across their parts of the platform.Build scalable backends for LanceDB Enterprise to support user and agent experiences across billion-scale datasets.Our tech stack: Rust, Typescript, React, Python, k8s, Terraform, CSPs
Qualifications
8+ years as a software engineerExperience working on frontend and backend parts of large-scale data platforms (e.g., databases, data infra, ML/AI systems), including work on concurrency and multitenancyExperience crafting UIs using Typescript, React/next.js/Vercel, CLIs, and APIsExperience building elegant user-oriented and agent-oriented experiencesExperience building infrastructure with CSP stacks, Terraform, and k8sDemonstrated ownership of ambiguous projects with minimal guidanceStrong written and verbal communication (can drive alignment across teams)Comfortable using data (metrics, experiments, usage) to guide decisionsExperience contributing to or working with open source communities
Please apply for this role only if you meet all of the above qualifications, and agree with the day-to-day responsibilities.
About LanceDB
LanceDB is a developer-friendly, open-source data platform for multimodal AI. From hyper-scalable vector search to advanced retrieval for RAG, from streaming training data to interactive exploration of large-scale datasets, LanceDB is the best foundation for your AI workloads.
Other open roles at LanceDB(3)
LanceDB is the first open-source AI-Native Multimodal Lakehouse. Build fast, reliable RAG, agents, and search engines with a multimodal vector database with native versioning and S3-compatible object storage.
Key team members

David Wang

Dave Unger

Peter Ebert

Catherine Chung
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