Senior Customer Success Engineer

About the role

LanceDB is a high-performance, open-source, cloud-native data platform designed for AI-native and multimodal workflows. It powers advanced applications in machine learning and data infrastructure.

Responsibilities

• Partner with customers to design, deploy, and optimize LanceDB in production environments.
• Provide technical guidance on system configuration, query optimization, and integration patterns.
• Identify and resolve adoption barriers, troubleshoot complex distributed-system issues, and coordinate with product and engineering teams.
• Own customer success metrics, including deployment time, usage growth, retention, and satisfaction.
• Develop and deliver technical enablement materials, such as sample code, automation tools, and documentation.
• Communicate with internal teams to influence product development and improve developer experience.
• Collaborate with sales engineering and support engineering to address customer needs and escalate issues.
• Contribute to internal tooling, runbooks, and playbooks to support the growing customer success organization.
• Help shape processes, tooling, and team culture as LanceDB scales its customer success and post-sales engineering capabilities.

Requirements

• 10+ years of professional experience in technical roles such as post-sales engineering, customer success, solutions architecture, or technical support, preferably in data infrastructure or distributed systems.
• Proven track record supporting or deploying distributed database systems or large-scale cloud-native data platforms.
• Strong proficiency in Rust and Python, with the ability to read, debug, and write production-grade code in both languages.
• Deep understanding of distributed systems concepts, including sharding, replication, consensus, partitioning, failure recovery, and performance tuning.
• Experience deploying and managing workloads on Kubernetes or similar container orchestration frameworks, and familiarity with cloud environments (AWS, GCP, Azure).
• Exceptional communication and presentation skills, able to engage with customers' engineering leaders, architects, and executives with credibility and empathy.
• Strong problem-solving ability, with a customer-first mindset and the ability to operate autonomously in fast-moving, ambiguous environments.
• Willingness and ability to flex across functions, including pre-sales engineering, technical support, and post-sales enablement, as needed by the business.

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.