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LanceDB

Open-source, serverless vector database for AI

Senior Support Engineer

Full-Time
$180k - $250k/yr
Expert
United States
In Person
Customer Experience & SupportCustomer Support

About the job

Requirements
  • At least 8 years of professional experience in a support, operations, or troubleshooting role in a distributed database or data infrastructure environment.
  • Demonstrated experience with distributed database systems, cloud-native data platforms such as AWS, GCP, or Azure, and Kubernetes or serverless deployment models.
  • Strong knowledge of distributed systems concepts, including sharding, replication, consensus, failure modes, resource contention, performance bottlenecks, and cloud-native orchestration such as Kubernetes, containerization, and autoscaling.
  • Demonstrated experience with at least one of vector or feature stores, analytics engines, or big data systems.
  • Comfort reading logs and correlating them with source code, working with Grafana dashboards, and creating shell scripts or Python code to assist in debugging.
  • Ability to explain complex technical issues clearly to customers, manage expectations, and advocate for customers.
  • Ability to prioritize under pressure and work closely with engineering teams to drive issue resolution.
  • Comfort working in a fast-moving startup environment with high autonomy and evolving responsibilities.
Responsibilities
  • Build 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 for support response times, resolution times, and customer satisfaction, and help build a scalable support organization.
  • Identify recurring issues, escalate product bugs or user-experience gaps, propose support-process improvements, and advocate for customers in the product roadmap.
  • Serve as a primary technical point of contact for customers by troubleshooting issues, responding to escalations, and guiding customers through full-lifecycle support for large-scale deployments of LanceDB.
  • Collaborate with engineering and product teams to reproduce issues, debug root causes, propose remediation, and drive fixes or enhancements.
  • Investigate distributed database internals, including query execution, storage engines, indexing, sharding, replication, failover, and cloud orchestration for Kubernetes and serverless-style deployments.
  • Use and contribute to Rust codebases by reproducing customer environments, inspecting logs, building diagnostic tools, running instrumentation, and applying patches and configuration changes.
Desired Qualifications
  • Proficiency in Rust, including reading, navigating, and debugging code; production-quality Rust systems experience is preferred.
  • Familiarity with storage engine internals, indexing and 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, including logging and observability tools such as Prometheus, Grafana, and OpenTelemetry, as well as alerting and SLOs/SLAs.
  • Previous experience creating runbooks, selecting and configuring support ticketing systems, and defining incident response processes.

About the company

LanceDB is an open-source vector database designed for AI applications, storing and managing high-dimensional vectors and multimodal data. It runs serverlessly with a compute-storage split to lower costs and offers multiple indexing options, including vector indexes, for fast queries; it provides hybrid search by combining semantic and full-text search as point lookups inside the database. Its open-core model plus a managed cloud (LanceDB Cloud) for enterprises gives it a cost-aware and scalable option compared to traditional managed databases. The goal is to provide developers with a production-ready, scalable, and cost-efficient datastore for AI embeddings and multimodal data, enabling easy deployment and integration for AI-powered apps.

Company Size

51-200

Company Stage

Series A

Total Funding

$38.1M

Headquarters

San Francisco, California

Founded

2022

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Simplify's Take

What believers are saying

  • Series A closed July 22, 2026, led by Theory Ventures and Databricks Ventures.
  • Hugging Face integration and DuckDB SQL retrieval expanded distribution during 2026.
  • Reverie Summit on August 11, 2026, positioned LanceDB inside physical-AI and world-model spending.

What critics are saying

  • Open-source usage can commoditize LanceDB before Enterprise monetization matures in 2026.
  • Databricks, Snowflake, and OpenSearch already bundle adjacent retrieval features, squeezing LanceDB adoption.
  • If LanceDB misses enterprise-scale reliability, customers like ByteDance shift critical workloads elsewhere.

What makes LanceDB unique

  • LanceDB’s Lance format powers multimodal data, with v0.38.0 released August 31, 2026.
  • CrewAI rebuilt agent memory on LanceDB, citing 2B+ executions on August 3, 2026.
  • ByteDance Volcano Engine used Lance for 100K+ QPS and seven-day-to-one-day pipelines.

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Benefits

  • Remote Work Options
  • Hybrid Work Options
  • Flexible Work Hours
  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Wellness Program
  • Mental Health Support
  • Professional Development Budget
  • Conference Attendance Budget
  • Stock Options
  • Company Equity

Growth & Insights and Company News

Headcount

6 month growth

3%

1 year growth

3%

2 year growth

3%
LanceDB
Jun 25th, 2025
LanceDB Raises $30M Series A to Build the Multimodal Lakehouse

We have closed another funding round to accelerate development of the Multimodal Lakehouse - a unified platform for AI data infrastructure.

India Pioneer
Jun 24th, 2025
LanceDB Secures $30 Million to Scale Multimodal AI Infrastructure

Bengaluru, June 24, 2025 - LanceDB, an open-source platform designed to handle large-scale multimodal AI workloads, has raised $30 million in its latest funding round.

Finimize
Jun 24th, 2025
LanceDB Secures $30M Series A Funding

LanceDB has secured $30 million in Series A funding to enhance its AI data platform, with major investors like Theory Ventures and Y Combinator participating. The funding will support LanceDB's efforts to integrate multimodal data types, such as text, video, images, and audio, which are crucial for advancing AI capabilities. This investment reflects confidence in LanceDB's strategy to help enterprises manage complex data workflows, essential for future AI models.

SiliconANGLE Media
May 15th, 2024
LanceDB raises $8M to speed up AI models with its open-source vector database

LanceDB raises $8M to speed up AI models with its open-source vector database - SiliconANGLE

TechCrunch
May 15th, 2024
LanceDB, which counts Midjourney as a customer, is building databases for multimodal AI

Backed by Y Combinator, LanceDB this month raised $8 million in a seed funding round led by CRV, Essence VC and Swift Ventures, bringing its total raised to $11 million.