Technical Lead, Data Systems & Infrastructure

Posted 3 Days Ago
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San Francisco, CA
Hybrid
Senior level
Information Technology • Natural Language Processing • Productivity • Software • Automation
The AI assistant for enterprise sellers, starting with automated account research.
The Role
Lead the architecture and scaling of data infrastructure for an AI-driven CRM. Design data models, mentor teammates, and optimize systems for performance and reliability.
Summary Generated by Built In

About Lightfield

Lightfield is a new kind of CRM.

It's a collaborative system for founders to find, understand, and serve customers faster than anything before it.

It captures every customer interaction, generates and performs followup actions, and answers questions about your go-to-market using knowledge obtained in real time.

Our system is tuned and customized by a team of experienced sellers, engineers, and researchers. Many of us worked on large-scale products including Llama, Messenger, Instagram, Pinterest, and Linkedin before this.

Lightfield.app

About the role

We’re looking for an experienced, creative, and versatile technical leader to define and scale the data infrastructure and retrieval systems that power Lightfield’s AI-driven CRM.

Your work will enable real-time insights, intelligent automation, and seamless customer interactions, making our CRM fast, intuitive, and indispensable.

What you’ll do

  • Architect and scale the data infrastructure, search, and retrieval systems that power Lightfield’s AI-driven CRM.

  • Design and optimize data models and indexing strategies to support CRM workflows, AI-driven insights, and contextual search.

  • Build and maintain full-stack systems, end-to-end, ensuring reliability, scalability, and performance.

  • Develop observability and metrics to enable smooth operation, proactive issue detection, and continuous improvement.

  • Mentor teammates, participate in code reviews, and help shape engineering culture and practices.

  • Contribute to building a world-class engineering team through recruiting, mentorship, and knowledge-sharing.

Who you are

  • 10+ years of experience in development, with a strong background in infrastructure, data modeling, and backend systems.

  • Deep experience building scalable, high-performance data infrastructure that supports large-scale data processing and retrieval.

  • Strong understanding of database design, indexing strategies, and query optimization, especially in PostgreSQL or similar relational databases.

  • Experience with full-text search infrastructure (e.g., Typesense) to enable fast, structured query capabilities.

  • Experience with vector search and semantic retrieval (e.g., Pinecone) to support AI-driven contextual understanding and recommendations.

  • Experience with graph databases (e.g., Neo4j) to model complex relationships is a plus.

  • You’re excited about Large Language Models (LLMs) and the opportunity to build systems that leverage them for search, retrieval, and automated insights.

  • You have the ability to ramp quickly on tech stack that currently features TypeScript, React, Next.js, Node.js, Apollo GraphQL, and PostgreSQL, Typesense, and Pinecone.

  • Strong fundamentals in software engineering, with a degree in Computer Science or a related field.

  • Thrives in ambiguity, able to independently drive projects and deliver results in a fast-moving environment.

  • Clear communicator, capable of articulating technical decisions to both technical and non-technical stakeholders.

  • Passionate about building products customers love, ensuring our CRM is intuitive, intelligent, and indispensable.

Top Skills

Apollo Graphql
Neo4J
Next.Js
Node.js
Pinecone
Postgres
React
Typescript
Typesense
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The Company
HQ: San Fransisco, CA
70 Employees
Hybrid Workplace
Year Founded: 2020

What We Do

Tome is an AI assistant for enterprise sellers, built to automate manual work and enable more effective conversations throughout the entire sales cycle.

The Tome platform trains custom language models on your company’s sales methodology, value framework, and GTM tech stack, allowing AEs to:

1. Book more qualified pipeline with automated account and persona research, suggested value hypotheses, and personalized outreach messages for the highest priority accounts.

2. Accelerate existing pipeline with detailed meeting prep, generated collateral, AI note taking synced to your CRM, and automated follow-ups.

3. Optimize their sales playbook with insights on which messages, features, and collateral lead to bigger, faster deals.

In this new world, AEs can focus less on work that weighs them down and more on spending time with customers. Sales leaders can ensure quality pipeline creation is maximized, more deals are won, and reps ramp faster. And RevOps leaders are at peace-of-mind knowing their systems and processes are being used to their full potential.

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