About the job
Forward Deployed Engineer – LanceDB
Location: San Francisco Bay Area (In-Person / Hybrid)
Team: Engineering
Job Type: Full-Time
About LanceDB
At LanceDB, we are pioneering the future of data management with our open-source, cloud-native vector database and multimodal AI lakehouse. Our platform is designed using a high-performance columnar format, empowering developers and businesses to create scalable, real-time search and analytics applications that integrate vectors, structured data, and AI workflows seamlessly. With options for both embedded and managed deployment models, alongside rich SDKs in Rust, Python, and other programming languages, LanceDB is expertly crafted to enhance state-of-the-art retrieval, feature engineering, and large-scale AI systems.
Role Overview
Join our dynamic Engineering team as a Forward Deployed Engineer (FDE). In this pivotal role, you will bridge the gap between deep systems engineering and direct customer engagement. You will collaborate closely with our strategic clients in the Bay Area to architect, deploy, and optimize LanceDB in high-demand production settings.
This is a highly technical, product-facing role. You will not only solve customer challenges but also contribute production-quality code and valuable insights back to LanceDB’s core product lines. Your practical experience in deploying LanceDB alongside modern data infrastructures will play a crucial role in shaping our product architecture, APIs, and overall performance.
What You’ll Do
Lead on-site and remote technical deployments of LanceDB with enterprise clients, focusing on architecture design, performance tuning, and operational stability.
Develop and maintain production-grade code in Rust and Python for customer integrations and internal tools.
Contribute code upstream to LanceDB’s core repositories, including bug fixes, feature enhancements, and architectural adjustments based on client needs.
Gather and relay structured product feedback from customer interactions to product and engineering teams, shaping future roadmaps and designs.
Integrate LanceDB into existing data and AI infrastructure stacks like Spark and Ray.
Troubleshoot and resolve complex challenges related to distributed systems and cloud environments.

