The open-source database for AI applications
LanceDB, headquartered in San Francisco, California, is an open-source database designed specifically for AI applications. It provides hyper-scalable vector search capabilities and advanced retrieval for retrieval-augmented generation (RAG), making it ideal for developers working with large-scale AI...
Employees at LanceDB enjoy competitive salaries, equity options, flexible remote work policies, and generous PTO to promote work-life balance....
LanceDB fosters a culture of innovation and collaboration, prioritizing developer experience and open-source contributions. The team values transparen...
LanceDB • San Francisco
Location: San Francisco Bay Area (In-Person / Hybrid)
Team: Engineering
Job Type: Full-Time
LanceDB is an open-source, cloud-native vector database and multimodal AI lakehouse built on a high-performance columnar format. It enables developers and enterprises to build scalable, real-time search and analytics applications across vectors, structured data, and AI workflows. LanceDB delivers both embedded and managed deployment models with rich SDKs in Rust, Python, and other languages, and is purpose-built to power state-of-the-art retrieval, feature engineering, and large-scale AI systems.
As a Forward Deployed Engineer (FDE) at LanceDB, part of the Engineering organization, you will operate at the intersection of deep systems engineering and direct customer engagement. You will work hands-on with strategic customers in the Bay Area to design, deploy, and scale LanceDB in demanding production environments.
This is a highly technical, product-facing role. You will not only deliver customer solutions, but also contribute production-quality code and actionable feedback directly back to LanceDB’s core product lines. Your real-world experience deploying LanceDB alongside modern data infrastructure will directly influence product architecture, APIs, and performance characteristics.
Lead on-site and remote technical deployments of LanceDB with enterprise and strategic customers, including architecture design, benchmarking, performance tuning, and operational hardening.
Write and maintain production-grade code in Rust and Python for customer integrations, SDK enhancements, ingestion pipelines, and internal tooling.
Contribute code upstream to LanceDB’s core repositories, including bug fixes, performance improvements, new features, and architectural refinements informed by customer use cases.
Capture, distill, and communicate structured product feedback from customer engagements to product and core engineering teams, influencing roadmap and design decisions.
Integrate LanceDB into existing data and AI infrastructure stacks, including Spark, Ray, and similar distributed processing frameworks.
Diagnose and resolve complex issues involving distributed systems, cloud object storage, concurrency, and large-scale data movement.
Partner closely with product, core engineering, and GTM teams to ensure customer requirements translate into generalizable, reusable platform capabilities.
Deliver technical deep dives, workshops, and proofs-of-concept for engineers and architects at customer organizations.
At least 2 years of experience in a technical field or forward deployed engineering role.
Ability and willingness to be on-site at customers daily. This role is located in the San Francisco Bay Area, and candidates must live there. No exceptions will be made for this requirement.
Proven experience building, deploying, or operating distributed, cloud-native databases or data platforms in production.
Strong proficiency in Rust and Python, with a demonstrated ability to write performant, maintainable systems code.
Hands-on familiarity with data infrastructure technologies such as Apache Spark, Ray, or similar distributed compute and data processing frameworks.
Experience integrating databases with batch and streaming data pipelines, ML workflows, or large-scale analytics systems.
Demonstrated ability to contribute directly to core product codebases, not just customer-specific glue or scripts.
Deep understanding of distributed systems concepts including sharding, replication, consistency, concurrency, and failure handling.
Strong customer-facing skills, with the ability to work directly with engineers, architects, and technical leaders to drive solutions from concept to production.
Experience with vector databases, similarity search, or multimodal data systems.
Prior contributions to open-source databases, storage engines, or distributed systems projects.
Familiarity with cloud platforms (AWS, GCP, Azure), Kubernetes, Terraform, and observability tooling.
Experience with Apache Arrow–based ecosystems, large-scale ML data pipelines, or AI infrastructure stacks.
As a Forward Deployed Engineer at LanceDB, you’ll work directly with cutting-edge customers while shaping the core product itself. Your field experience will feed back into LanceDB’s architecture, APIs, and performance roadmap, giving you a rare opportunity to influence both customer success and the evolution of next-generation AI data infrastructure.
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