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Generative AI Engineer — Creator Tools

Claire Dupont

Full-time · Mid-level · Los_Angeles

About the role

We build tools for independent creators — specifically the ones doing this full time and treating it like a business. Not the mega-influencers with management teams. The 50,000 creators making between $80k and $400k per year on YouTube, Substack, TikTok, and Patreon who spend a disproportionate amount of their week on the business side: responding to brand partnership emails, writing contracts, managing their content calendar, handling refund requests from subscribers, and trying to figure out why a video underperformed. We've built an AI layer on top of those workflows and 14,000 creators pay us monthly to use it. Our stack is Python, FastAPI, LangChain, and Postgres. We're fully remote, we don't do daily stand-ups, and we ship fast — not because we're careless, but because our users notice when we're slow. We're looking for a Generative AI Engineer who cares about making genuinely useful software for independent workers, who is good at building LLM features that handle edge cases gracefully, and who can tell the difference between a demo that looks impressive and a feature that actually helps someone finish work faster.

Responsibilities

  • Build and ship new AI features in our creator workflow product — drafting, contract analysis, audience Q&A, and content performance analysis
  • Own the RAG pipeline that grounds AI outputs in each creator's historical content and platform data
  • Design evaluation workflows to measure output quality and catch regressions before users do
  • Collaborate with our single product designer on UX decisions that affect how AI outputs are presented
  • Write clean, well-tested backend code that your teammates can extend and maintain

Requirements

  • 3+ years of software engineering with at least 1 year building LLM-powered features that real users depend on
  • LangChain for building multi-step agentic workflows — you've debugged LangChain in production, not just in a notebook
  • OpenAI API experience: structured outputs, function calling, streaming, and managing token budgets at scale
  • RAG pipeline design and implementation — retrieval strategy, chunking, re-ranking, and evaluation
  • Python — async, clean, pragmatic code that handles real user data
  • Prompt Engineering as a systematic practice — you build evaluation sets, run variants, and measure what changes

Benefits

  • Your work is used daily by people earning their living independently — the feedback loop is immediate and honest
  • Full remote, async-first
  • $100,000 – $122,000 base salary + equity
  • $1,000 annual creator economy research budget — yes, we will pay you to study the people you're building for
  • No mandatory meetings before 10am in any time zone

Job Type

Full-time

Level

Mid-level

Language

English

Salary Range

$100,000 – $122,000

AI Expertise

NLP & Prompt Engineering

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