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Design and maintain distributed Lance dataset operations, develop high-performance indices and data formats, and improve query performance across Spark, Ray, and Trino. Contribute Rust-based table formats and encodings, integrate Lance with major open-source data infrastructure systems, operate internal data processing infrastructure, and promote the project through open-source communities and conferences.

Own system-level testing for Lance and LanceDB across correctness, reliability, scalability, performance, data integrity, fault recovery, upgrades, and compatibility. Build automated test frameworks, realistic workloads, fault-injection scenarios, performance and soak tests, and reproducible CI environments. Investigate failures using logs, metrics, traces, and source code, create minimal reproductions, and partner with engineers on fixes. Apply AI tools responsibly to accelerate test development, failure analysis, and debugging.

Create and maintain developer documentation, tutorials, API references, troubleshooting guides, and runnable examples for LanceDB. Build documentation designed for both developers and AI agents, validate AI-generated content, maintain documentation tooling, automate code and link checks, and collaborate with engineering, product, and open-source communities. The role requires strong Python skills, database and data workflow knowledge, technical writing expertise, and experience with Git-based development workflows.

As a Senior Solutions Engineer, you will engage in pre-sales conversations, design architecture, and deliver demos to help customers integrate LanceDB's AI solutions.

Own LanceDB’s product direction by shaping the roadmap with technical leadership, researching users and competitors, gathering continuous user insight, and driving cross-functional prioritization. The role partners closely with engineering as a technically respected peer, defines product changes for AI and data-platform users, uses metrics and experiments to guide decisions, and operates with high ownership in an ambiguous environment.

Build LanceDB’s revenue marketing function and enterprise demand engine from the ground up. Own account-based marketing strategy, segmentation, campaigns, content, account planning, martech implementation, pipeline reporting, and partner co-marketing. Identify high-intent accounts through open-source and product-usage signals, create tailored omnichannel programs, and collaborate closely with founders, Sales, RevOps, and Partners to source and influence enterprise pipeline.

Lead technical partner enablement and co-delivery for LanceDB: onboard and train partner engineers, run PoCs and architecture reviews, author reference architectures and deployment blueprints, relay partner feedback to product, and support GTM and thought-leadership activities to scale partner integrations.