About LanceDB LanceDB is a high-performance, open-source, cloud-native database built for AI-native and multimodal workflows. From vector search at multi-billion-scale to real-time retrieval, feature engineering, and analytics across large-scale datasets, LanceDB powers cutting-edge applications of machine learning and data infrastructure.

We’re building the next generation of intelligent, data-driven systems — and we’re looking for an experienced, customer-focused engineer who can help our enterprise users deploy, operate, and scale LanceDB successfully.

Your Role As the Senior Customer Success Engineer , you will be a trusted advisor to our most strategic customers. You’ll combine deep technical expertise with outstanding communication and relationship-building skills to ensure customers achieve success in deploying and scaling LanceDB across production workloads.

You’ll guide customers from onboarding through adoption and expansion — while flexing seamlessly into pre-sales or technical support capacities as business needs require. You’ll serve as the connective tissue between our customers, product, and engineering teams, driving continuous improvement in both the customer experience and the product itself.

In This Role, You Will

• Partner closely with customers to design, deploy, and optimize LanceDB in production environments, ensuring reliability, scalability, and performance for distributed, cloud-native workloads.

Must-have What We’re Looking For

• 10+ years of professional experience in technical roles such as post-sales engineering, customer success, solutions architecture, or technical support, ideally within the data infrastructure or distributed systems space.
• Proven track record supporting or deploying distributed database systems or large-scale cloud-native data platforms (e.g., high-availability, multi-region, and horizontally scalable environments).

Nice-to-have

• Previous experience as a founding or early member of a customer success or solutions engineering function at a high-growth startup.
• Hands-on experience with vector search, feature stores, or AI-native data systems.
• Contributions to open-source projects (especially in Rust or Python) or experience authoring developer-facing technical content.
• Familiarity with modern observability stacks (Prometheus, Grafana, OpenTelemetry) and incident management best practices.
• Experience designing or leading enterprise architecture workshops or technical proof-of-concepts.

Why Join Us You’ll join a world-class team of open-source builders (co-authors of pandas, and contributors to HDFS, Arrow, Iceberg, and HBase) working on cutting-edge AI infrastructure. You’ll collaborate on systems that power next-generation AI workloads while shaping how LanceDB operates and scales production environments.