LanceDB

• Build and own the RevOps function end to end—systems, processes, data, and reporting—across the full sales and customer success lifecycle. • Own our CRM and GTM tech stack (HubSpot plus supporting sales tooling): administration, data hygiene, workflow automation, and integrations. • Establish consistent CRM adoption and data discipline across the team—defining the process, standards, and habits that make our data trustworthy in the first place. • Design and run forecasting, pipeline management, and deal-desk processes that give leadership an accurate, real-time view of the business. • Own the deal desk: track deals to closure, quarterback the steps required to get contracts signed, and proactively remove blockers so nothing stalls. • Coordinate deal execution across functions—facilitating legal redlines, navigating customer procurement and vendor onboarding, and driving internal approvals and pricing/discount sign-off. • Partner with sales and CS leadership on territory, quota, and capacity planning as the team scales. • Instrument the post-sale motion—renewals, expansion, and account health—so customer success can act on the right signals at the right time. • Lay the groundwork for meaningful GTM reporting—defining the metrics that will matter and building toward a single source of truth as our data foundation matures. • Evaluate, implement, and rationalize sales and CS tooling, ensuring the stack scales with the company rather than fighting it. • Identify friction in the funnel and drive cross-functional process improvements between sales, CS, marketing, and finance.

• Serve as the technical lead in pre-sales conversations—partnering with account executives to scope, solution, and articulate the value of LanceDB for customer-specific workflows. • Lead technical discovery and architecture design sessions with prospects across verticals including AI infra, LLM ops, and multimodal data pipelines. • Build and deliver custom demos and proof-of-concepts to highlight how LanceDB solves challenging RAG, vector search, and feature engineering problems. • Act as the bridge between customer pain points and our engineering/product teams—informing roadmap priorities with real-world feedback. • Partner closely with design partners and early adopters to ensure successful onboarding and expansion. • Champion a superior developer experience with a sharp focus on documentation, SDK ergonomics, and integration workflows.

• Lead technical onboarding, training programs, and certifications for partner engineers • Partner with alliances and field teams to support proofs-of-concept and design reviews • Author and maintain partner-facing technical assets • Act as the primary technical liaison between partners and internal teams • Participate in joint business planning and support regional marketing events • Drive ecosystem adoption by sharing best practices through technical blogs and presentations

Role Description 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. - Partner closely with customers to design, deploy, and optimize LanceDB in production environments, ensuring reliability, scalability, and performance for distributed, cloud-native workloads. - Lead technical onboarding and architecture reviews; provide best-practice guidance on system configuration, query optimization, and integration patterns. - Proactively identify adoption barriers, troubleshoot complex distributed-system issues, and coordinate with product and engineering teams to drive timely resolutions. - Own customer success metrics: deployment time, usage growth, retention, and satisfaction. Build dashboards and track health across accounts. - Develop and deliver technical enablement: create sample code, automation tools, and documentation to accelerate customer outcomes. - Serve as the customer’s technical advocate internally — communicating feature requests, influencing roadmap priorities, and improving developer experience. - Collaborate cross-functionally with sales engineering (for technical evaluations, proofs-of-concept, and demos) and support engineering (for escalations and issue triage). - Contribute to internal tooling, runbooks, and playbooks that will form the foundation of LanceDB’s future customer success organization. - Help to shape processes, tooling, and team culture as we scale customer success and post-sales engineering. Qualifications - 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). - Strong proficiency in Rust and Python — able to read, debug, and write production-grade code in both languages. - Deep understanding of distributed systems concepts: sharding, replication, consensus, partitioning, failure recovery, and performance tuning. - Experience deploying and managing workloads on Kubernetes or other container orchestration frameworks, and familiarity with cloud environments (AWS, GCP, Azure). - Exceptional communication and presentation skills: able to engage directly with customers’ engineering leaders, architects, and executives with credibility and empathy. - Strong problem-solving ability, coupled 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. Requirements - 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. Benefits You’ll join a world-class team of open-source builders 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.

• Our first security-focused engineer • Takes high-level direction (e.g., "identify top five security-related gaps for AX") and drives to results • Success looks like a LanceDB platform that follows security-related best practices, and an ongoing partnership with other engineers to continuously enhance our security posture in all areas of the product • Select, deploy and tune security tooling across all relevant repos and environments, ensuring full coverage • Identify and remediate security-related risks, including but not limited to cloud IAM, access controls, product vulnerabilities • Own vulnerability management, from running our CVE program through closely working with other engineers on specific remediations • Support periodic evidence collection and control testing for compliance commitments • Apply relevant industry trends, best practices, and specific vulnerabilities to our product

• Shape roadmap with CTO + eng leadership • Deep dives into competitors, users, and adjacent tech • Talk to users constantly; turn insight into product changes • Drive cross-team decisions on priorities (eng, field, support) • Work with engineering directly as a technically-respected peer

• Creating the most compelling experience for users to explore and manage their multimodal data. • Closely working with the rest of the team and designers to optimize user experience. • Building scalable backends for LanceDB Cloud that offer a serverless experience for billion-scale datasets. • Fast pace with a stellar team of core contributors to incredible projects like Python Pandas, Arrow, Delta-rs, Hadoop, to define the next generation data system for AI. • Future leadership opportunities as the team grows. • Be the driving force to raise the bar and strive for better architecture and best practices within the company.

• As one of the early team members, build our support infrastructure and practices while handling customer cases: • Develop and maintain knowledge-base articles, runbooks, and support tooling that document common issues, best practices, deployment patterns, and performance tuning. • Contribute to metrics around support response-times, resolution times, customer satisfaction, and help build a scalable support organization as we grow. • Work proactively: identify recurring issues, escalate product bugs or UX gaps, propose improvements in the support process, and advocate for the customer in the roadmap. • Serve as one of the primary technical points of contact for our customers: troubleshoot issues, respond to escalations, and guide customers through full lifecycle support for large-scale deployments of LanceDB. • Work in close collaboration with our engineering and product teams to reproduce issues, debug root causes, propose remediation, and drive fixes or enhancements. • Dive deeply into distributed database internals: query execution, storage engine, indexing, sharding, replication, fail-over, and cloud orchestration (Kubernetes, serverless-style deployments). • Use and contribute to Rust codebases: reproduce customer environments, inspect logs, build diagnostic tools, run instrumentation, apply patches and configuration changes.