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LanceDBLA

Field Engineer — Deploy AI Data Infrastructure

LanceDB is an open-source, developer-friendly multimodal vector database and AI lakehouse designed for scalable RAG, agents, and search applications.

LanceDB

Employee count: 11-50

United States only

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A cutting-edge technology firm seeks a skilled Forward Deployed Engineer to facilitate the deployment of LanceDB with enterprise customers in the Bay Area. This role involves leading technical deployments, writing production-grade code in Rust and Python, and providing customer-focused engineering solutions. Ideal candidates should demonstrate proficiency in distributed systems, cloud-native databases, and possess strong technical communication skills. This position offers the opportunity to influence product evolution while working with a diverse range of industries.
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About LanceDB

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AI applications have outgrown the data infrastructure built for yesterday. Today's complex workloads demand more than traditional data lakes or vector databases - they need a foundation built for multimodal AI at scale. LanceDB exists to solve this fundamental gap, creating a unified platform that can handle embeddings, documents, images, and video all in one place, enabling teams to build AI applications faster, cheaper, and with dramatically reduced infrastructure complexity.

By 2025, an estimated 156 zettabytes of data will be video - representing 90% of all data generated. The Multimodal Lakehouse combines the best of data lakes and vector databases into a single platform optimized for AI workloads, eliminating the need for multiple disparate systems. Leading AI companies like Runway, Midjourney, and Character.ai rely on LanceDB to search over tens of billions of vectors and manage petabytes of training data, proving that the future of AI infrastructure must be built to handle the richness, scale, and velocity of multimodal data.

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LanceDB

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