Senior Solutions Engineer

LanceDB; United States; On-site; USD 130,000 - 170,000; Full time

Job summary

LanceDB is seeking a Senior Solutions Engineer in the United States to bridge cutting‑edge AI engineering with real‑world business use cases. You will design solutions, deliver demos, and craft integrations that demonstrate LanceDB’s strengths in production environments.

You will lead pre‑sales discussions, guide discovery and architecture sessions, and translate technical requirements into scalable architectures for customers across industries.

Qualifications

• 5+ years in a Sales Engineer, Solutions Engineer, ML Engineer, or AI Infrastructure role.
• Strong knowledge of AI/ML frameworks (PyTorch, TensorFlow) and how they integrate with infrastructure for training, fine‑tuning, and inference.
• Hands‑on experience with distributed systems (Ray, Spark, Kubernetes).
• Familiarity with cloud services (AWS, GCP, Azure) including compute and storage (EC2, GKE, S3).
• Confident communicating with technical and non‑technical stakeholders and translating complex infrastructure into actionable solutions.

Responsibilities

• Serve as the technical lead in pre‑sales conversations, scoping and articulating LanceDB's value for customer workflows.
• Lead technical discovery and architecture sessions with prospects across AI infra, LLM ops, and multimodal data pipelines.
• Build and deliver custom demos and proofs‑of‑concepts showcasing LanceDB solutions for RAG, vector search, and feature engineering.
• Bridge customer pain points with engineering/product teams and inform roadmap priorities.
• Partner with design partners and early adopters to ensure onboarding and expansion.
• Champion developer experience with documentation, SDK ergonomics, and integration workflows.

Skills

AI/ML frameworks

Distributed systems

Cloud services

Stakeholder communication

Pre-sales & solutions engineering

Tools

Ray

Spark

Kubernetes

Terraform

Docker

CI/CD

Prometheus

Grafana

Job description

About LanceDB

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.

About the Role

We are looking for a Senior Solutions Engineer 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.

Your Responsibilities Will Include

• 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.

Requirements

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

• 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.

Bonus Points If You

• 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.

About the LanceDB Team

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.