LanceDB
Forward Deployed Engineer – LanceDB
Location:
San Francisco Bay Area (In-Person / Hybrid) Team:
Field Engineering Job Type:
Full-Time
About LanceDB LanceDB is an open-source, cloud-native vector database and multimodal AI lakehouse built on a high-performance columnar format. It enables developers and enterprises to build scalable, real-time search and analytics applications across vectors, structured data, and AI workflows. LanceDB delivers both embedded and managed deployment models with rich SDKs in Rust, Python, and other languages, and is purpose-built to power state-of-the-art retrieval, feature engineering, and large-scale AI systems.
Role Overview As a
Forward Deployed Engineer (FDE)
at LanceDB, part of the
Field Engineering
organization, you will operate at the intersection of deep systems engineering and direct customer engagement. You will work hands-on with strategic customers in the Bay Area to design, deploy, and scale LanceDB in demanding production environments.
This is a
highly technical, product-facing role . You will not only deliver customer solutions, but also contribute production-quality code and actionable feedback directly back to LanceDB’s core product lines. Your real-world experience deploying LanceDB alongside modern data infrastructure will directly influence product architecture, APIs, and performance characteristics.
What You’ll Do
Lead
on-site and remote technical deployments
of LanceDB with enterprise and strategic customers, including architecture design, benchmarking, performance tuning, and operational hardening.
Write and maintain
production-grade code in Rust and Python
for customer integrations, SDK enhancements, ingestion pipelines, and internal tooling.
Contribute code upstream
to LanceDB’s core repositories, including bug fixes, performance improvements, new features, and architectural refinements informed by customer use cases.
Capture, distill, and communicate
structured product feedback
from customer engagements to product and core engineering teams, influencing roadmap and design decisions.
Integrate LanceDB into existing
data and AI infrastructure stacks , including Spark, Ray, and similar distributed processing frameworks.
Diagnose and resolve complex issues involving
distributed systems , cloud object storage, concurrency, and large-scale data movement.
Partner closely with product, core engineering, and GTM teams to ensure customer requirements translate into
generalizable, reusable platform capabilities .
Deliver technical deep dives, workshops, and proofs-of-concept for engineers and architects at customer organizations.
What We’re Looking For
Proven experience building, deploying, or operating
distributed, cloud-native databases or data platforms
in production.
Strong proficiency in Rust and Python , with a demonstrated ability to write performant, maintainable systems code.
Hands‑on familiarity with
data infrastructure technologies
such as
Apache Spark, Ray , or similar distributed compute and data processing frameworks.
Experience integrating databases with batch and streaming data pipelines, ML workflows, or large-scale analytics systems.
Demonstrated ability to
contribute directly to core product codebases , not just customer‑specific glue or scripts.
Deep understanding of distributed systems concepts including sharding, replication, consistency, concurrency, and failure handling.
Strong customer‑facing skills, with the ability to work directly with engineers, architects, and technical leaders to drive solutions from concept to production.
Nice-to-Have
Experience with vector databases, similarity search, or multimodal data systems.
Prior contributions to open‑source databases, storage engines, or distributed systems projects.
Familiarity with cloud platforms (AWS, GCP, Azure), Kubernetes, Terraform, and observability tooling.
Experience with Apache Arrow–based ecosystems, large‑scale ML data pipelines, or AI infrastructure stacks.
Why LanceDB? As a Forward Deployed Engineer at LanceDB, you’ll work directly with cutting‑edge customers while shaping the core product itself. Your field experience will feed back into LanceDB’s architecture, APIs, and performance roadmap, giving you a rare opportunity to influence both customer success and the evolution of next‑generation AI data infrastructure.
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San Francisco Bay Area (In-Person / Hybrid) Team:
Field Engineering Job Type:
Full-Time
About LanceDB LanceDB is an open-source, cloud-native vector database and multimodal AI lakehouse built on a high-performance columnar format. It enables developers and enterprises to build scalable, real-time search and analytics applications across vectors, structured data, and AI workflows. LanceDB delivers both embedded and managed deployment models with rich SDKs in Rust, Python, and other languages, and is purpose-built to power state-of-the-art retrieval, feature engineering, and large-scale AI systems.
Role Overview As a
Forward Deployed Engineer (FDE)
at LanceDB, part of the
Field Engineering
organization, you will operate at the intersection of deep systems engineering and direct customer engagement. You will work hands-on with strategic customers in the Bay Area to design, deploy, and scale LanceDB in demanding production environments.
This is a
highly technical, product-facing role . You will not only deliver customer solutions, but also contribute production-quality code and actionable feedback directly back to LanceDB’s core product lines. Your real-world experience deploying LanceDB alongside modern data infrastructure will directly influence product architecture, APIs, and performance characteristics.
What You’ll Do
Lead
on-site and remote technical deployments
of LanceDB with enterprise and strategic customers, including architecture design, benchmarking, performance tuning, and operational hardening.
Write and maintain
production-grade code in Rust and Python
for customer integrations, SDK enhancements, ingestion pipelines, and internal tooling.
Contribute code upstream
to LanceDB’s core repositories, including bug fixes, performance improvements, new features, and architectural refinements informed by customer use cases.
Capture, distill, and communicate
structured product feedback
from customer engagements to product and core engineering teams, influencing roadmap and design decisions.
Integrate LanceDB into existing
data and AI infrastructure stacks , including Spark, Ray, and similar distributed processing frameworks.
Diagnose and resolve complex issues involving
distributed systems , cloud object storage, concurrency, and large-scale data movement.
Partner closely with product, core engineering, and GTM teams to ensure customer requirements translate into
generalizable, reusable platform capabilities .
Deliver technical deep dives, workshops, and proofs-of-concept for engineers and architects at customer organizations.
What We’re Looking For
Proven experience building, deploying, or operating
distributed, cloud-native databases or data platforms
in production.
Strong proficiency in Rust and Python , with a demonstrated ability to write performant, maintainable systems code.
Hands‑on familiarity with
data infrastructure technologies
such as
Apache Spark, Ray , or similar distributed compute and data processing frameworks.
Experience integrating databases with batch and streaming data pipelines, ML workflows, or large-scale analytics systems.
Demonstrated ability to
contribute directly to core product codebases , not just customer‑specific glue or scripts.
Deep understanding of distributed systems concepts including sharding, replication, consistency, concurrency, and failure handling.
Strong customer‑facing skills, with the ability to work directly with engineers, architects, and technical leaders to drive solutions from concept to production.
Nice-to-Have
Experience with vector databases, similarity search, or multimodal data systems.
Prior contributions to open‑source databases, storage engines, or distributed systems projects.
Familiarity with cloud platforms (AWS, GCP, Azure), Kubernetes, Terraform, and observability tooling.
Experience with Apache Arrow–based ecosystems, large‑scale ML data pipelines, or AI infrastructure stacks.
Why LanceDB? As a Forward Deployed Engineer at LanceDB, you’ll work directly with cutting‑edge customers while shaping the core product itself. Your field experience will feed back into LanceDB’s architecture, APIs, and performance roadmap, giving you a rare opportunity to influence both customer success and the evolution of next‑generation AI data infrastructure.
#J-18808-Ljbffr