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 a driven, creative engineer who is excited about the challenge of leveraging LLMs to build exceptionally innovative product experiences.
You’ll join us at the frontier of AI product development, developing industry-leading approaches to solve important customer problems.
Engineers at Lightfield own and drive projects from inception to impact, working with teammates of all functions along the way.
You’ll also push our company’s overall product and technical vision as we learn from each project and continue to scale.
What you’ll do
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Collaborate with product leaders to identify customer problems, scope requirements, and implement LLM-powered solutions.
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Apply LLMs as reasoning engines to build domain-specific AI assistants.
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Create and enhance prompts, applying techniques like few-shot learning and chain-of-thought.
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Develop and optimize end-to-end RAG pipelines and agent architectures to leverage public and proprietary data.
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Improve end-to-end AI agent quality (e.g. relevance, fidelity, latency) via empirical evaluation and iteration.
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Build and enhance systems and tools that enable high-velocity experimentation (e.g. LLM-powered automated evaluation) and customized product experiences.
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Stay at the forefront of AI research and incorporate state-of-the-art techniques.
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Shape technical direction and best practices for AI application development at Lightfield.
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Help build a world-class engineering team by recruiting and mentoring teammates.
Who you are
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You have the ability to ramp quickly on tech stack that features TypeScript, React, Next.js, Node.js, Apollo GraphQL, and Aurora PostgreSQL.
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You have explored working with LLMs, either through professional projects or personal experimentation.
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You have a degree in Computer Science or a related field, with a strong foundation in software engineering principles.
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You are familiar with AI and ML concepts (e.g. training, evaluation techniques).
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You are passionate about keeping up with and exploring the latest advancements in LLMs and LLMOps (including open source solutions, e.g. LangChain).
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You are excited to develop new best practices in an emerging domain.
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You can drive a project with an ambiguous problem independently.
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You enjoy strategically balancing ambitious vision with frequent delivery of user value.
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You are able to clearly communicate your reasoning and decisions to your teammates (technical and nontechnical) at an appropriate altitude of detail.
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You are energized by building software experiences customers will use directly and depend on to do their jobs successfully.
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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.
