About LanceDB 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.
About
the Role As a Senior Partner Solutions Architect (PSA) , 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.
What You'll Do Partner Enablement & Training: Lead technical onboarding, training programs, and certifications for partner engineers and architects. Equip them to independently deliver and support LanceDB implementations. Joint Architecture & Co-Delivery: 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. Scalable Technical Content: Author and maintain partner-facing technical assets, including production-ready reference architectures, integration guides, deployment blueprints (Terraform, Docker), and sample code. Product & Ecosystem Advocate: 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. Go-To-Market (GTM) Collaboration: Participate in joint business planning and support regional technical marketing events, hackathons, and campaigns alongside channel account managers. Thought Leadership: 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).
What We're Looking For Must-Have
Qualifications: Experience: 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. Ecosystem Familiarity: 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. Technical Depth: Deep understanding of distributed systems concepts (sharding, replication, partitioning, and performance tuning) and container orchestration (Kubernetes, cloud object storage). Programming Skills: Strong proficiency in Python and a willingness to dive into Rust (or vice versa) to read, debug, and write production-grade integration code or SDK extensions. Communication: Exceptional presentation and communication skills. You can translate complex data infrastructure into actionable solutions for audiences ranging from partner developers to C-level executives. Startup Agility: A self-starter mindset with the ability to thrive and operate autonomously in fast-moving, ambiguous environments.
Bonus Points If You Have: Hands-on experience building or supporting vector search pipelines, RAG applications, feature stores, or multimodal AI architectures. 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).
Why Join Us 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 a new open-source vector database that can support low-latency billion-scale vector search on a single node. Built around a new columnar data format, LanceDB makes it incredibly easy to build applications for generative AI, recsys, search engines, content moderation, and more.
Salary
$180,000 - $250,000
Location
Remote
Experience
10+ years
Total raised
$500K
Last stage
Seed
Investors
Chang She
Chang She
Co-founder and CEO
Lei Xu
CTO
No applications, no recruiter spam. Just the intro.
A few questions to make sure this role is the right shape for you. Two minutes.
I write the intro, send it to the founder, and handle the back-and-forth.
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.