L
LanceDBvia Ashby
Senior Support Engineer
Americas timezones$180K - $250K/yrPosted 3mo ago
OtherSeniorFull-time#ai-lab
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About the Role
About LanceDB
LanceDB is a high-performance, open-source, cloud-native database built for multimodal workflows. From vector search at multi-billion scale to real-time retrieval, feature engineering, and analytics across large-scale datasets, LanceDB powers AI data infrastructure.
We’re looking for a hands-on, technically strong Support Engineer who will be the bridge between our engineering team and enterprise users of LanceDB, helping our customers debug distributed databases built in Rust.
YOUR ROLE
- 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.
WHAT WE’RE LOOKING FOR
MUST-HAVE (PLEASE DO NOT APPLY UNLESS YOU MEET ALL OF THE CRITERIA IN THIS SECTION)
- 8+ years of professional experience in a support / operations / troubleshooting role in a distributed database or data infrastructure environment.
- Demonstrated experience with distributed database systems, cloud-native data platforms (AWS, GCP, or Azure), and Kubernetes or serverless deployment models.
- Strong knowledge of distributed systems concepts: sharding, replication, consensus, failure modes, resource contention, performance bottlenecks, and cloud-native orchestration (Kubernetes, containerization, autoscaling).
- Demonstrated experience with at least one of the following: vector/feature stores, analytics engines or big data systems.
- Very comfortable with reading logs and correlating them with source code, working with Grafana dashboards, and creating shell scripts or Python code to assist in debugging.
- Excellent customer-facing communication skills: you’ll be working directly with high-value customers, so you must be comfortable explaining complex technical issues clearly, managing expectations, and advocating for the customer.
- Strong sense of ownership, urgency, correct prioritization under pressure, and ability to work closely with engineering teams to drive resolution.
- Comfortable working in a fast-moving startup environment with high autonomy and evolving responsibilities.
NICE-TO-HAVE
- Proficiency in Rust: you should be comfortable reading, navigating, and debugging code; ideally you’ve built or debugged production-quality systems written in Rust.
- Familiarity with storage engine internals, indexing/data layout, performance tuning, and profiling tools.
- Contributions to open-source projects (especially Rust), or experience writing diagnostic tools, debuggers, or instrumentation.
- Experience deploying and monitoring systems in large-scale production environments: logging/observability (e.g., Prometheus, Grafana, OpenTelemetry), alerting, SLOs/SLAs.
- Previous experience creating new runbooks, selecting and configuring support ticketing systems, and defining incident response processes.
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 work together on building systems that support next-generation AI workloads, while helping define how LanceDB runs and scales in production infrastructure at some of the most innovative companies of our time.
LanceDB is a high-performance, open-source, cloud-native database built for multimodal workflows. From vector search at multi-billion scale to real-time retrieval, feature engineering, and analytics across large-scale datasets, LanceDB powers AI data infrastructure.
We’re looking for a hands-on, technically strong Support Engineer who will be the bridge between our engineering team and enterprise users of LanceDB, helping our customers debug distributed databases built in Rust.
YOUR ROLE
- 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.
WHAT WE’RE LOOKING FOR
MUST-HAVE (PLEASE DO NOT APPLY UNLESS YOU MEET ALL OF THE CRITERIA IN THIS SECTION)
- 8+ years of professional experience in a support / operations / troubleshooting role in a distributed database or data infrastructure environment.
- Demonstrated experience with distributed database systems, cloud-native data platforms (AWS, GCP, or Azure), and Kubernetes or serverless deployment models.
- Strong knowledge of distributed systems concepts: sharding, replication, consensus, failure modes, resource contention, performance bottlenecks, and cloud-native orchestration (Kubernetes, containerization, autoscaling).
- Demonstrated experience with at least one of the following: vector/feature stores, analytics engines or big data systems.
- Very comfortable with reading logs and correlating them with source code, working with Grafana dashboards, and creating shell scripts or Python code to assist in debugging.
- Excellent customer-facing communication skills: you’ll be working directly with high-value customers, so you must be comfortable explaining complex technical issues clearly, managing expectations, and advocating for the customer.
- Strong sense of ownership, urgency, correct prioritization under pressure, and ability to work closely with engineering teams to drive resolution.
- Comfortable working in a fast-moving startup environment with high autonomy and evolving responsibilities.
NICE-TO-HAVE
- Proficiency in Rust: you should be comfortable reading, navigating, and debugging code; ideally you’ve built or debugged production-quality systems written in Rust.
- Familiarity with storage engine internals, indexing/data layout, performance tuning, and profiling tools.
- Contributions to open-source projects (especially Rust), or experience writing diagnostic tools, debuggers, or instrumentation.
- Experience deploying and monitoring systems in large-scale production environments: logging/observability (e.g., Prometheus, Grafana, OpenTelemetry), alerting, SLOs/SLAs.
- Previous experience creating new runbooks, selecting and configuring support ticketing systems, and defining incident response processes.
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 work together on building systems that support next-generation AI workloads, while helping define how LanceDB runs and scales in production infrastructure at some of the most innovative companies of our time.
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