LanceDB is a developer-friendly, open source database for multimodal AI. From hyper scalable vector search to advanced retrieval for RAG, from streaming training data to  interactive exploration of large scale AI datasets, LanceDB is the best foundation for your AI application. 

LanceDB

Equity / Stock Options

LanceDB is a developer-friendly, open-source data lake for multimodal AI. From hyper-scalable vector search to advanced retrieval for RAG, from streaming training data to interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application, and powers some of the most groundbreaking applications and challenging requirements today. LanceDB is building the multimodal lakehouse for AI — an open-source, developer-friendly database (powered by the Lance columnar format) that companies like Midjourney and Harvey rely on to build production-scale AI applications.

As a founding recruiter at LanceDB, you will be responsible for scaling our team by building and standardizing our recruiting process and leading end-to-end hiring. You’ll partner directly with founders and leadership to define hiring strategy, attract and hire exceptional talent. You'll own our recruiting platform and tools, design a hiring engine that delivers a great candidate experience, and drive impactful, high-velocity talent initiatives — sourcing, engaging, and closing top-tier talent spanning engineering, product, sales, marketing, and other business functions. We're a remote-native company hiring across the United States and just beginning to expand globally, so you'll help shape how we find and hire great people across time zones and, increasingly, borders. This is an opportunity to build a world-class recruiting function from the ground up and help define the culture of a fast-growing, open-source-first startup.

Build, standardize, and continuously improve LanceDB's end-to-end hiring  process across both technical and GTM roles — from sourcing and screening to closing candidates.

Own our recruiting platform and tech stack (ATS, sourcing, and AI recruiting tools), defining and optimizing the systems that let hiring scale with the team.

Design and deliver an exceptional candidate experience at every stage, ensuring a fast, consistent, and high-signal process that reflects our brand and works for candidates across time zones.

Recruit for deeply technical roles — systems and database engineers, many working in Rust — alongside go-to-market roles across sales, marketing, developer relations, and customer success.

Partner closely with hiring managers in engineering and GTM to define role requirements, craft compelling job descriptions, and standardize a structured interview process tailored to each function.

Proactively source candidates through direct outreach, team referrals, open-source communities, hackathons, and other industry events.

8+ years of experience in recruiting, preferably in a fast-growing startup environment or technical companies.

A track record of building and standardizing recruiting processes from the ground up, with a bias toward operational excellence.

Hands-on experience owning and optimizing applicant tracking systems (ATS) and AI recruiting tools.

Proven ability to source and execute creative talent attraction strategies; close high-caliber candidates across both technical and go-to-market roles.

A commitment to delivering a great candidate experience while running an impactful, high-velocity process.

Data-driven mindset with experience using recruiting analytics to improve hiring outcomes.

Comfort recruiting for deeply technical positions (e.g. infrastructure and database engineering) as well as sales, marketing, and other GTM functions.

Experience recruiting for a remote-native, distributed team; experience supporting international or multi-country hiring is a plus as we begin expanding globally.

Passion for startup culture and the ability to thrive in a fast-paced, dynamic environment.

A strong communicator who can effectively sell the vision of LanceDB to potential hires.

Excellent stakeholder management, communication, and negotiation skills.

Bonus: familiarity with the AI/ML, data infrastructure, or developer-tools ecosystem.

Timezone Match Required

Startup Experience

Experience

LanceDB is seeking a Founding Recruiter to build and standardize their end-to-end hiring process. The role involves partnering with leadership to scale technical and GTM teams, managing the recruiting tech stack, and sourcing top-tier talent for a remote-native AI data lake company.

Founding Recruiter

Full Time

LanceDB is a developer-friendly, open-source data lake for multimodal AI. From hyper-scalable vector search to advanced retrieval for RAG, from streaming training data to interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application, and powers some of the most groundbreaking applications and challenging requirements today.

We're looking for our first Revenue Operations Lead to build the operational backbone of our go-to-market motion from the ground up. This is a hands-on, founding role: you'll own the systems, data, and processes that power our sales and customer success teams, and you'll turn a fast-moving startup GTM effort into a repeatable, measurable machine.

You'll partner directly with sales and CS leadership to design pipeline and forecasting discipline, instrument our tooling, run the deal desk, and give leadership a clear, trustworthy view of the business. You'll be the person who keeps deals moving—shepherding them from verbal yes to signed contract by unblocking legal, procurement, and internal approvals. As LanceDB scales, this role is positioned to grow into building and leading a broader RevOps team.

This is ideal for a builder who's energized by ambiguity, comfortable moving fast, and equally happy configuring HubSpot and driving day-to-day adoption as they are shaping GTM strategy. This role rewards ingenuity: piecing together a clear picture from incomplete data today, while architecting the reliable foundation that makes that unnecessary tomorrow. It's a rare chance to build the thing, not just operate it.

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.

You thrive in a fast-paced, startup environment and enjoy working with high-caliber teams.

5+ years of experience in Revenue Operations, Sales Operations, or a closely related GTM operations role.

Hands-on experience building or scaling RevOps at an early-stage or high-growth startup—you've done the work yourself, not just managed people who did.

Deep hands-on expertise with HubSpot (or a comparable CRM) as an administrator, plus experience with the broader sales tooling ecosystem (e.g., outbound, conversation intelligence, enrichment, CPQ/deal-desk tools).

A foundation-builder's mindset: you're motivated by creating process and data discipline where little exists today, and you understand that reliable analytics come after the plumbing is in place—not before.

Working knowledge of forecasting, pipeline management, and GTM reporting. Analytical skills are welcome, but for now they'll be applied to building the data foundation rather than mining a mature one.

Experience running a deal desk or owning deal execution—shepherding contracts to signature, coordinating legal redlines, and navigating customer procurement and vendor onboarding processes.

Comfortable operating across both sales and customer success motions.

Excellent communicator who can partner with GTM leadership and translate operational detail into actionable insight for executives.

Based in the US and able to work effectively in a remote environment.

Have experience in developer tools, open source, or data/AI infrastructure companies.

Have supported both sales-led and product-led (PLG) go-to-market motions.

Are comfortable in SQL or BI tools (e.g., Looker, Metabase, dbt) for deeper GTM analytics.

Have designed comp plans, quota models, or territory frameworks.

Have built RevOps from zero as a first hire before.

Have partnered closely with finance on GTM analytics, board metrics, or capacity planning.

Senior Level

LanceDB is seeking a Revenue Operations Lead to build the operational backbone of their go-to-market motion. The role involves owning the CRM (HubSpot), designing pipeline and forecasting processes, and managing the deal desk to scale sales and customer success efforts. This is a founding role ideal for a builder with experience in early-stage startups.

Revenue Operations Lead

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.
We’re building the next generation of intelligent, data-driven systems — and we’re looking for an experienced, customer-focused engineer who can help our enterprise users deploy, operate, and scale LanceDB successfully.

, 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.
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.

 internally — communicating feature requests, influencing roadmap priorities, and improving developer experience.

 (for technical evaluations, proofs-of-concept, and demos) and 

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.

 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 

 (e.g., high-availability, multi-region, and horizontally scalable environments).

 — able to read, debug, and write production-grade code in both languages.

: sharding, replication, consensus, partitioning, failure recovery, and performance tuning.

Experience deploying and managing workloads on 

 or other container orchestration frameworks, and familiarity with 

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.

 — including pre-sales engineering, technical support, and post-sales enablement — as needed by the business.

Previous experience as a founding or early member of a 

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.

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.

LanceDB is seeking a Senior Customer Success Engineer to help enterprise users deploy and scale its cloud-native data platform. The role involves designing production environments, leading technical onboarding, and troubleshooting distributed system issues using Rust, Python, and Kubernetes. You will act as a technical advisor and bridge between customers and the engineering team.

Americas Engineering

Senior Customer Success Engineer

Bonus

 is a developer-friendly, open-source data lake for multimodal AI. From hyper-scalable vector search to advanced retrieval for RAG, from streaming training data to interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application, and powers some of the most groundbreaking applications and challenging requirements today.

 who blends deep technical understanding of AI/ML infrastructure with excellent communication and solution-building skills. In this role, you will serve as a trusted advisor to prospective customers, design partners, and strategic accounts—bridging the gap between cutting-edge AI engineering and real-world business use cases.

This role is ideal for someone who thrives at the intersection of technical depth and customer interaction, and who enjoys crafting solutions, demos, and integrations that showcase LanceDB’s strengths in production environments.

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.

You have 5+ years of experience in a Sales Engineer, Solutions Engineer, ML Engineer, or AI Infrastructure role, supporting AI/ML products or platforms.

Strong knowledge of AI/ML frameworks like PyTorch or TensorFlow, and how they integrate with infrastructure for model training, fine-tuning, and inference.

Hands-on experience working with distributed systems such as Ray, Spark, or Kubernetes.

Familiarity with cloud services (AWS, GCP, Azure) including compute and storage (e.g., EC2, GKE, S3).

Confident communicating with both technical and non-technical stakeholders, and able to translate complex infrastructure into actionable solutions.

You must be based out of the San Francisco Bay Area

, and be willing to travel to customer sites as needed.  This position is only available to candidates that fulfill this criteria.

Have experience building or supporting feature engineering workflows or vector search pipelines.

Have worked with feature stores (e.g., Feast, Tecton) or have designed custom ML feature pipelines.

Have experience in observability and monitoring (Prometheus, Grafana, ELK/EFK).

Are familiar with open-source data/streaming frameworks such as Apache Spark, Flink, Delta Lake, Kafka, or Airflow.

Have deep Python skills or are curious about Rust.

Are comfortable creating technical content, workshops, or presenting at meetups/conferences.

Have experience deploying ML infrastructure in customer environments using tools like Terraform, Docker, and CI/CD pipelines.

Have supported enterprise customers or worked in a customer-facing technical capacity before.

LanceDB was created by experts with decades of experience building tools for data science and machine learning. From co-authors of pandas to Apache PMC of HDFS, Arrow, Iceberg and HBase, the LanceDB team has created open-source tools used by millions worldwide.

Travel Required

Senior Solutions Engineer at LanceDB. This role involves leading pre-sales technical conversations, designing AI/ML infrastructure solutions, and building custom demos for RAG and vector search. The ideal candidate will bridge the gap between AI engineering and business use cases using technologies like PyTorch, TensorFlow, and distributed systems such as Ray and Kubernetes.

$180K – $250K • Offers Equity • Offers Commission

Senior Solutions Engineer

Competitive compensation

LanceDB is a high-performance, developer-friendly, open-source data lake built for multimodal AI. From hyper-scalable vector search at a multi-billion scale to advanced retrieval for RAG, streaming training data, and real-time analytics, LanceDB powers some of the most groundbreaking applications and challenging AI infrastructure requirements today.

We are building the next generation of intelligent, data-driven systems—and we’re looking for a strategic, customer-focused engineer to build, enable, and scale our global partner ecosystem.

, you will sit at the intersection of product engineering, business development, and customer success. You will be the trusted technical advisor to LanceDB’s strategic partner ecosystem, including global System Integrators (SIs), Cloud Service Providers (AWS, GCP, Azure), Technology Alliances, and AI/ML orchestration platforms.

Your mission is to enable, empower, and unblock our partners so they can successfully architect, deploy, and scale LanceDB solutions on behalf of their enterprise customers. This role requires a unique blend of deep technical grit (distributed systems, AI/ML pipelines) and exceptional relationship-building skills to drive mutual growth and technical excellence.

 Lead technical onboarding, training programs, and certifications for partner engineers and architects. Equip them to independently deliver and support LanceDB implementations.

 Partner with alliances and field teams to support high-value proofs-of-concept (PoCs), design reviews, and architectural validations for complex, cloud-native enterprise environments.

 Author and maintain partner-facing technical assets, including production-ready reference architectures, integration guides, deployment blueprints (Terraform, Docker), and sample code.

 Act as the primary technical liaison between our partners and LanceDB’s internal Product and Engineering teams. Synthesize partner-sourced feedback and feature requests to directly influence our roadmap.

 Participate in joint business planning and support regional technical marketing events, hackathons, and campaigns alongside channel account managers.

 Drive ecosystem adoption by sharing best practices through technical blogs, whitepapers, open-source contributions, and presentations at major industry conferences (e.g., AWS re:Invent, AI meetups).

 10+ years of professional experience in customer- or partner-facing technical roles (e.g., Solutions Architecture, Partner Engineering, Sales Engineering, or ML Infrastructure), ideally supporting data platforms or distributed systems.

 Proven track record working with or within a partner ecosystem (SIs, cloud providers, or technology alliances) with a firm grasp of how partners take solutions to market.

 Deep understanding of distributed systems concepts (sharding, replication, partitioning, and performance tuning) and container orchestration (Kubernetes, cloud object storage).

 (or vice versa) to read, debug, and write production-grade integration code or SDK extensions.

 Exceptional presentation and communication skills. You can translate complex data infrastructure into actionable solutions for audiences ranging from partner developers to C-level executives.

 A self-starter mindset with the ability to thrive and operate autonomously in fast-moving, ambiguous environments.

Hands-on experience building or supporting 

vector search pipelines, RAG applications, feature stores,

Experience with open-source data frameworks and infrastructure orchestration tools (e.g., Apache Spark, Ray, Delta Lake, Terraform, Kafka, or Airflow).

Familiarity with modern observability and monitoring stacks (Prometheus, Grafana, OpenTelemetry) for troubleshooting distributed workloads.

Active contributions to open-source communities or a portfolio of developer-facing technical content (blogs, tutorials, GitHub repositories).

You’ll join a world-class team of open-source builders working at the absolute forefront of AI infrastructure. In this role, you won't just support existing workflows—you will actively define how the entire AI ecosystem integrates with, deploys, and scales LanceDB across the enterprise.

We offer competitive compensation, comprehensive benefits, and a highly collaborative culture dedicated to developer experience and engineering excellence.

LanceDB is seeking a Senior Partner Solutions Architect to enable and scale its global partner ecosystem. The role involves providing technical leadership for strategic partners, designing cloud-native architectures, and collaborating with product teams to integrate multimodal AI and vector search capabilities. Key technologies include Python, Rust, and distributed systems.

Partner Solutions Architect

 is a developer-friendly, open-source database for multimodal AI. From hyper-scalable vector search to advanced retrieval for RAG, from streaming training data to interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application, and powers some of the most groundbreaking and challenging applications today.

We’re seeking an experienced Fullstack Engineer to join our world-class team, polishing the user experience of the frontier of high-performance vector databases in the cloud.

Creating the most compelling experience for users to explore and manage their multimodal data.

Closely working with the rest of 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.

Our tech stack: Typescript, React, Python, Rust, AWS / Google Cloud / Azure / K8s / Terraform

You have at least 6 years of experience in developing front-end applications.

You have a thorough understanding of Typescript, React/Next.js/Vercel, HTML, CSS, and can independently work with designers to build stunning applications.

You have worked on both frontend UIs as well as backend applications, and the plumbing in-between.

You’re obsessed with giving users the best end-to-end experience possible

You care about simplicity, code quality and performance

You like working with a small, fast-paced, high-caliber team with a lot of autonomy

You have significant experience working with vector databases and/or distributed databases.

You are an open-source veteran, contributed to Open Source TypeScript projects.

Familiar with cloud-native technology, such as K8s, AWS Lambda, and Terraform.

Experience with large-scale and high-traffic systems.

LanceDB was created by experts with decades of experience building tools for data science and machine learning. From co-authors of Pandas to Apache PMC of HDFS, Arrow, Iceberg and HBase, the LanceDB team has created open source tools used by millions world-wide.

LanceDB is seeking a Senior Fullstack Engineer to develop a high-performance vector database for multimodal AI. The role involves building scalable backends and optimizing the user experience using TypeScript, React, Python, and Rust. Candidates will work on serverless experiences for billion-scale datasets across AWS, Google Cloud, and Azure.

Senior UX/AX Engineer

Senior Fullstack Engineer

Learning & Development Budget

Flexible Working Hours

Open Source Contribution Budget

 is the preeminent data platform for multimodal AI use cases. From hyper-scalable vector search to advanced retrieval for RAG, from streaming training data to interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application, and powers some of the most groundbreaking applications and challenging requirements today.


 to help expand the reach of Lance and LanceDB within the broader data infrastructure ecosystem. You’ll work at the intersection of high-performance computing, big data, and open-source systems.  You will contribute scale and performance improvements, integrations with the wider data and AI ecosystem,  simplifying distributed operations, and usability and maintainability enhancements.


Designing and maintaining efficient distributed Lance dataset operations

Building efficient indices to enable predicate pushdown and accelerate queries in Spark, Ray, or Trino

Working on table formats, data encodings, and various aspects of the Lance format in Rust

Driving open-source community efforts to integrate the Lance format with Spark, Hive Metastore, Presto, Trino, Ray, and other data infrastructure systems

Operating and improving internal data processing infrastructure

Promoting the Lance format in open-source communities and at Big Data conferences

10+ years of experience building high-performance databases, big data systems, or large-scale data services

Deep understanding of internals of open-source Big Data or AI training systems (e.g., Hadoop, Spark, Flink, Ray, Iceberg, Delta Lake, Hudi, ClickHouse, Trino, Presto, PyTorch, or JAX)

Strong experience with high-performance computing in C++, Java, and/or Scala

Experience with Rust (or willingness to learn it)

Proven ability to move fast, work independently, and collaborate with a high-caliber team

Contributor, committer, or PMC member in Apache or other large open-source projects

Experience with Apache Arrow, DataFusion, Parquet, Iceberg, or Delta Lake

Track record of driving large features or integrations in distributed systems

Strong community presence and passion for open-source collaboration

A key role shaping an open-source project with real production usage

Competitive compensation, equity, and benefits

Generous learning budget and support for open-source contributions

You’ll join a world-class team of open-source builders, including co-authors of pandas, and contributors to HDFS, Arrow, Iceberg, and HBase.  You’ll collaborate on systems that power next-generation AI workloads while shaping how LanceDB operates and scales production environments.

LanceDB is seeking a Senior Software Engineer to enhance its multimodal AI data platform. The role involves designing distributed dataset operations and building efficient indices using Rust, Java, and C++. You will drive open-source integrations with systems like Apache Spark and Ray to improve scale and performance.

Timezone Matching

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