Support Engineer

San Francisco · Toronto Hub · 3+ years experience · Full-time · Onsite · Posted Sep 29, 2026

At a glance

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.
We hit 8 figures in ARR in year one and more than doubled it in year two. We have 180k+ GitHub stars, putting us in the top 50 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, working out of SF HQ and our new Toronto Hub. 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.

Firecrawl is seeking a hands-on Support Engineer to diagnose complex API issues and build systems that automate support for a fast-growing customer base.
The role acts as a technical bridge between users and the product, requiring the ability to own work end-to-end and advocate for customer needs with Engineering and Product teams.

Act as the first line of technical support for high-value and enterprise accounts.
Diagnose API errors, failed scrapes, crawls, blocked sites, authentication problems, and rate limits.
Reproduce issues, escalate confirmed bugs with clear context, and manage resolution.
Review customer workflows and integration plans to suggest reliable, maintainable improvements.
Triage a busy queue across Slack, email, and chat while determining urgency and human vs. AI intervention.
Advocate for customer needs to shape bug fixes and API improvements.
Automate repeated questions and manual steps using AI triage, drafted replies, and smart routing.
Build lightweight internal tools such as debugging scripts, dashboards, and agents.
Improve AI support agent knowledge sources and review agent performance.
Write troubleshooting guides, runbooks, and documentation fixes.

3+ years of experience.
Strong fundamentals in APIs, HTTP, and debugging.
Proficiency in TypeScript or Python.
Product-minded with the ability to make priority and tradeoff decisions autonomously.
Experience using AI tools like Claude, Cursor, agents, and MCP servers.
Ability to explain technical ideas clearly and ask effective diagnostic questions.
Must be authorized to work in the United States or Canada.
Ability to work on-site five days a week in San Francisco or Toronto.

Experience in a technical customer-facing role such as support engineer, solutions engineer, developer support, or implementation specialist.
Experience supporting APIs, SDKs, or other developer tools.
Understanding of web scraping, browsers, and proxies.
Experience building with Firecrawl or similar web data platforms.
Experience shipping LLM-powered workflows in production.