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Lightfield

Software Engineer, Staff (Applied AI)

HQ: San Francisco$220k–$300kfulltimemidAdded 3 months ago

About this role

Lightfield, an AI-native CRM backed by top-tier VCs, seeks an AI Product Engineer to develop LLM-powered features that automatically organize customer interactions. You'll own projects from conception to impact, building intelligent assistants and RAG systems while shaping the technical direction of AI product development.

What you'll do

  • Collaborate with product leaders to identify problems and implement LLM-powered solutions
  • Build domain-specific AI assistants and optimize prompts using advanced techniques
  • Develop and enhance end-to-end RAG pipelines and agent architectures
  • Improve AI agent quality through empirical evaluation and iteration
  • Create tools enabling high-velocity experimentation and automated evaluation
  • Shape technical direction and mentor teammates on AI best practices

What they're looking for

  • LLM application development and prompt engineering
  • TypeScript, React, Next.js, Node.js
  • RAG pipelines and AI agent architectures
  • AI/ML concepts and evaluation techniques
  • GraphQL and Aurora PostgreSQL
  • Independent project ownership with ambiguous requirements
  • Technical and non-technical communication
  • LLMOps and tools like LangChain

Benefits

  • Competitive salary with meaningful early equity
  • Comprehensive health insurance (medical, dental, vision)
  • 3 weeks PTO plus 11 paid holidays and winter break
  • 3 months paid family leave
  • Remote work (Wednesdays), 401k, commuter and lunch stipends
  • Team events, dinners, and offsites
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Lightfield

Lightfield builds an AI-native CRM that automatically organizes customer interactions and powers sales teams through LLM-driven features and intelligent assistants. The company is hiring AI Product Engineers, Machine Learning Engineers, and Customer Success Engineers to develop full-stack AI capabilities, scale support systems, and shape the technical direction of their product.

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Likely interview questions

  • Can you walk us through a project where you've worked with LLMs? What techniques did you use to improve model quality or performance?
  • How would you approach building and evaluating a RAG pipeline for a CRM system that needs to extract insights from emails and calendar data?
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