# AI Enablement Lead at Firecrawl

AI Level 3, AI centrality 75 out of 100. Remote (San Francisco, CA).

## Details

- Company: [Firecrawl](https://jobsbylevel.com/companies/firecrawl)
- AI level: AI Level 3 (score 75 out of 100)
- Location: Remote (San Francisco, CA)
- Salary: $235k-$236k
- Posted: October 5, 2026
- Apply: https://jobsbylevel.com/go/d3cfe2f3-a57e-47e2-adba-0e28556e23d7

## Description

AI Enablement Lead Firecrawl is looking for someone to own how we use AI internally. The thesis behind the role: a company's output used to scale with headcount, and ours scales with tokens, meaning how much compute we run and how well we turn it into shipped work. A small team that does this well operates like one several times its size, and the ceiling on that isn't budget, it's adoption. You'll set up and maintain the agent harnesses, configs, and model routing every team runs on, revenue first, get the people who barely use agents onto them, and work straight from our token spend data to find who's burning it without output and who isn't using enough. Most of this work is people, not config. Getting someone to hand real work to an agent means asking them to change how they've worked for years, with tools that feel unfamiliar and sometimes threatening. You'll need EQ as much as technical depth: reading who's stuck and why, meeting people where they are, and staying with them until it sticks. You'll still live in the tools yourself, write the code when the harness falls short, and teach by showing. You'll be measured by who's using agents well now who wasn't before. Salary Range: $235,000–$260,000 USD/year Equity Range: Competitive equity. Details shared during the process. Location: San Francisco, CA (SF HQ). Hybrid, onsite 3+ days a week. Job Type: Full-Time Experience: 4+ years Work Authorization: Must be authorized to work in the United States. We're not able to sponsor US visas right now, though that may change down the line. About Firecrawl Firecrawl is the easiest way to turn the web into data AI agents can use. One API call converts any URL into clean, LLM-ready markdown or structured data. It's the boring-hard problem everyone building with LLMs eventually hits, solved. In September 2026, we raised a $75M Series B led by Smash Capital, and we're spending it building the largest repository of knowledge in the world. We hit 8 figures in ARR in year one and more than doubled it in year two. We have 187k+ GitHub stars, putting us in the top 40 repositories of all time, and developers, agents, and category-defining AI companies build on us every day. Growth like this is rare, and we're just getting started. We're a small team punching far above our weight. Everyone here owns a real piece of the product and company, end to end, and runs it themselves. No hiding behind process or headcount. This is a place for people who want to work at the frontier: an AI company building the infrastructure other AI companies run on, not one bolting AI onto an existing product. We move fast, go deep, and are building the tools superintelligence will rely on to gather data from the web. That library is called Alexandria, and it starts now. What You'll Do Own the internal AI stack: the agent harnesses, configs, shared skills, and model routing every team uses. Set them up, keep them sharp, and ship changes as the tools change Start with the revenue team. Learn how they actually work, find the jobs an agent should be doing, and get them running on it, then go team by team Bring people who barely use agents along. Sit with them, build their first real workflow together, handle the skepticism and the "I'm faster doing it myself" honestly, and stay on it until it sticks Work from our token spend data. Find who's burning tokens without output and who isn't using enough, then fix both. The second problem is usually the bigger one Make cost per useful token a number we manage: model choice, routing, caching, and cutting the workflows that don't pay for themselves Explain the why, over and over. Help every team understand what scaling with tokens means for their work and why it matters, in their language, not yours Build what's missing in code (MCP servers, hooks, evals, internal tooling), and track what's changing in Claude Code, Cursor, Codex, and whatever's next so we're working the new way the same week What We're Looking For You get why

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Source: https://jobsbylevel.com/jobs/ai-enablement-lead-at-firecrawl-57c4db

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