Senior Customer Success Engineer
šŗšø United States | šØš¦ Canada | š²š½ Mexico
Management
Python
Rust
Kubernetes
AWS
GCP
Azure
Machine Learning
Design
Sales
Analyst
Customer Support
$180K - $250K
Senior Customer Success Engineer
from šŗšø United States | šØš¦ Canada | š²š½ Mexico
$180K - $250K
About LanceDB
LanceDB is a high-performance, open-source, cloud-native data platform 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.
Weāre building the next generation of intelligent, data-driven systems ā and weāre looking for an experienced, customer-focused engineer who can help our enterprise users deploy, operate, and scale LanceDB successfully.
Your Role
As theSenior Customer Success Engineer, you will be a trusted advisor to our most strategic customers. Youāll combine deep technical expertise with outstanding communication and relationship-building skills to ensure customers achieve success in deploying and scaling LanceDB across production workloads.
Youāll guide customers from onboarding through adoption and expansion ā while flexing seamlessly intopre-sales or technical support capacities as business needs require. Youāll 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.
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 thecustomerās technical advocate internally ā communicating feature requests, influencing roadmap priorities, and improving developer experience.
Collaborate cross-functionally withsales engineering (for technical evaluations, proofs-of-concept, and demos) andsupport engineering (for escalations and issue triage).
Contribute to internal tooling, runbooks, and playbooks that will form the foundation of LanceDBās future customer success organization.
Help to shape processes, tooling, and team culture as we scale customer success and post-sales engineering.
What Weāre Looking For
Must-have:
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 deployingdistributed database systems or large-scalecloud-native data platforms (e.g., high-availability, multi-region, and horizontally scalable environments).
Strong proficiency inRust andPython ā able to read, debug, and write production-grade code in both languages.
Deep understanding ofdistributed systems concepts: sharding, replication, consensus, partitioning, failure recovery, and performance tuning.
Experience deploying and managing workloads onKubernetes or other container orchestration frameworks, and familiarity withcloud environments (AWS, GCP, Azure).
Exceptional communication and presentation skills: able to engage directly with customersā 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 toflex across functions ā including pre-sales engineering, technical support, and post-sales enablement ā as needed by the business.
Nice-to-have:
Previous experience as a founding or early member of acustomer success orsolutions engineering function at a high-growth startup.
Hands-on experience withvector search,feature stores, orAI-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 leadingenterprise architecture workshops ortechnical proof-of-concepts.
Why Join Us
Youāll join a world-class team of open-source builders working on cutting-edge AI infrastructure. Youāll collaborate on systems that power next-generation AI workloads while shaping how LanceDB operates and scales production environments.