AI Enablement Lead

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: Open to candidates already authorized to work in the US. We also support H-1B transfers, F-1 OPT and STEM OPT, TN (Canada and Mexico), and E-3 (Australia). We’re not able to sponsor new H-1B visas for candidates outside the US. 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 192k+ 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 scaling with tokens matters, and you can explain it to a salesperson, a lawyer, and an engineer in words each of them would use. A team that spends more on inference and ships more is winning. A team that spends more and doesn't isn't. You know how to tell the two apart You've rolled out coding agents or AI tooling across a team and can show what changed after. An adoption, not a pilot EQ. You can tell the difference between someone who's resisting and someone who's scared, and you know that most "I don't have time to learn this" is the second one. You bring people along without making them feel behind An engineer or a very technical operator who lives in Claude Code, Cursor, or Codex and writes code. When the harness is missing something, you build it You think about cost per useful token, and you've looked at spend data and changed something because of it You teach by showing. Pairing for an hour beats writing a guide nobody reads AI-pilled, bias to action, all in. You believe this is how work gets done now and you're already operating that way Often an ex-founder, an early startup engineer, or the person who led your last team through a tooling change nobody wanted and made it stick What We're NOT Looking For Prompt-tips influencers. A following built on "10 prompts that will change your life" isn't a track record Change-management consultants. You should be good at change management. You should not need a framework, a steering committee, or a deck to do it. We need the adoption, done by you, in the room IT admins. This isn't seat provisioning and license management Someone who wants to tell the team how to use AI without using it harder than anyone else here Someone who thinks the hard part is the tooling. The hard part is people A Note On Pace We operate at an absurd level of urgency because the w