Senior Customer Success Engineer

About the role

LanceDB is building a high-performance, open-source, cloud-native platform for multimodal AI and large-scale data workflows. We are seeking a technical expert to help our enterprise users deploy and scale our infrastructure within their production environments.

Key facts

What you'll do

• Partner with customers to design, deploy, and optimize LanceDB for distributed, cloud-native production workloads.
• Conduct technical onboarding and architecture reviews, providing guidance on configuration, integration, and query performance.
• Resolve complex distributed system issues and collaborate with internal engineering teams to address technical blockers.
• Manage customer success metrics including retention, usage growth, and deployment speed.
• Create technical resources such as sample code, automation scripts, and documentation to improve user outcomes.
• Represent the customer perspective internally to influence product roadmaps and feature prioritization.
• Work with sales and support teams on technical evaluations, proofs-of-concept, and issue escalation.
• Build internal playbooks and tooling to establish the foundation for our growing customer success department.

Requirements

• 10+ years of professional experience in customer success, solutions architecture, post-sales engineering, or technical support within data infrastructure or distributed systems.
• Demonstrated success deploying or supporting large-scale, cloud-native data platforms or distributed databases.
• Proficiency in Rust and Python with the ability to write and debug production code.
• Knowledge of distributed system fundamentals like sharding, replication, partitioning, consensus, and performance tuning.
• Experience managing workloads on Kubernetes or similar container orchestration tools across AWS, GCP, or Azure.
• Strong communication skills for engaging with technical leadership and executive stakeholders.
• Ability to work independently in a fast-paced environment while maintaining a customer-focused approach.

Nice to have

• Experience as an early or founding member of a solutions engineering or customer success team at a high-growth startup.
• Practical knowledge of AI-native data systems, vector search, or feature stores.
• History of contributing to open-source projects or creating technical content for developers.
• Familiarity with incident management and observability tools such as Grafana, Prometheus, or OpenTelemetry.
• Experience leading technical proof-of-concepts or enterprise architecture workshops.

Skills & tools

• Rust
• Python
• Kubernetes
• Distributed systems
• Cloud platforms (AWS, GCP, Azure)
• Observability stacks (Prometheus, Grafana, OpenTelemetry)

Practical notes

This is a remote position based in the Americas. The role requires flexibility to assist with pre-sales, support, and post-sales enablement as business needs evolve.