Full-Time

Senior Solutions Engineer

LanceDB

LanceDB

51-200 employees

Open-source, serverless vector database for AI

Compensation Overview

$180k - $250k/yr

San Francisco, CA, USA

In Person

Must be based in the San Francisco Bay Area and willing to travel to customer sites as needed.

Category
Sales & Solution Engineering (1)
Required Skills
Kubernetes
Rust
Microsoft Azure
Python
Grafana
Airflow
Distributed Systems
TensorFlow
PyTorch
Apache Spark
Machine Learning
Apache Kafka
Docker
RAG
AWS
Prometheus
Terraform
DevOps
Google Cloud Platform

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Requirements
  • Experience 5 or more years in a Sales Engineer, Solutions Engineer, Machine Learning Engineer, or Artificial Intelligence Infrastructure role supporting artificial intelligence or machine learning products or platforms.
  • Strong knowledge of artificial intelligence and machine learning frameworks such as PyTorch or TensorFlow, including their integration with infrastructure for model training, fine-tuning, and inference.
  • Hands-on experience with distributed systems such as Ray, Spark, or Kubernetes.
  • Familiarity with cloud services including Amazon Web Services, Google Cloud Platform, and Microsoft Azure, including compute and storage services such as EC2, GKE, and S3.
  • Ability to communicate with technical and non-technical stakeholders and translate complex infrastructure into actionable solutions.
  • Must be based in the San Francisco Bay Area and willing to travel to customer sites as needed.
Responsibilities
  • Serve as the technical lead in pre-sales conversations by partnering with account executives to scope, design solutions, and articulate the value of LanceDB for customer-specific workflows.
  • Lead technical discovery and architecture design sessions with prospects across artificial intelligence infrastructure, large language model operations, and multimodal data pipelines.
  • Build and deliver custom demonstrations and proof-of-concepts showing how LanceDB solves retrieval-augmented generation, vector search, and feature engineering problems.
  • Bridge customer pain points and engineering or product teams by informing roadmap priorities with real-world feedback.
  • Partner with design partners and early adopters to support successful onboarding and expansion.
  • Champion developer experience with a focus on documentation, software development kit ergonomics, and integration workflows.
Desired Qualifications
  • Experience building or supporting feature engineering workflows or vector search pipelines.
  • Experience with feature stores such as Feast or Tecton, or experience designing custom machine learning feature pipelines.
  • Experience with observability and monitoring tools such as Prometheus, Grafana, and ELK/EFK.
  • Familiarity with open-source data and streaming frameworks such as Apache Spark, Flink, Delta Lake, Kafka, or Airflow.
  • Deep Python skills or curiosity about Rust.
  • Experience creating technical content, workshops, or presentations at meetups or conferences.
  • Experience deploying machine learning infrastructure in customer environments using Terraform, Docker, and continuous integration/continuous delivery pipelines.
  • Experience supporting enterprise customers or working in a customer-facing technical capacity.

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 Jobs

Simplify's Take

What believers are saying

  • LanceDB raised $30 million in June 2025 from Theory Ventures and Databricks Ventures.
  • By mid-2026, LanceDB shipped DuckDB SQL retrieval, boosting adoption among analytics-heavy AI teams.
  • Midjourney, Runway, and Character.ai customer references validate enterprise demand for multimodal AI infrastructure.

What critics are saying

  • OpenSearch, Pinecone, and Weaviate compress LanceDB's vector-database differentiation inside twelve months.
  • Reliance on open-source adoption risks weak monetization unless enterprise conversions accelerate after the 2025 Series A.
  • If DuckDB or Hugging Face deepens native alternatives, LanceDB's platform becomes a format layer.

What makes LanceDB unique

  • LanceDB owns Lance, a multimodal lakehouse format tightly integrated with DuckDB and Hugging Face.
  • Its serverless architecture separates storage and compute, cutting AI retrieval costs on object stores.
  • Enterprise features target petabyte-scale data evolution, hybrid search, and multimodal workloads in production.

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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

401(k) Retirement Plan

401(k) Company Match

Phone/Internet Stipend

Home Office Stipend

Meal Benefits

Paid Vacation

Paid Sick Leave

Paid Holidays

Parental Leave

Family Planning Benefits

Fertility Treatment Support

Adoption Assistance

Childcare Support

Elder Care Support

Relocation Assistance

Pet Insurance

Gym Membership

Growth & Insights and Company News

Headcount

6 month growth

-5%

1 year growth

-2%

2 year growth

-14%
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.