Firecrawl is the web data API to search, scrape, and interact with the web at scale. Turn any source into clean Markdown or structured data your agents can ship with. Backed by Y Combinator.
About the role
Design, build, and operate GCP and on-prem infrastructure behind Firecrawl's products Run large stateful and high-throughput workloads on Kubernetes (search clusters, crawling fleets, queues, and databases) with zero-downtime upgrades
What they're looking for
- You've operated stateful distributed systems on Kubernetes at real scale, not just stateless services
- You have deep experience with a major cloud (GCP, AWS, or Azure), Docker, and Terraform. MLOps or ML-serving infrastructure experience (GPU workloads, model deployment pipelines) is a plus
- You've run large-scale, data-heavy systems in production: search platforms, crawling or ingestion pipelines, or comparable. Hands-on experience operating Vespa is a strong plus
- You care about latency, cost, and reliability in equal measure
- Experience with security and compliance infrastructure (SSO/SAML, audit logging, network isolation, SOC 2) is a strong plus
- You're comfortable owning ambiguous problems and turning them into shipped infrastructure
More about this role
You'll build the cloud infrastructure that turns the open web into data: the platform beneath Firecrawl's crawling, scraping, and search products. We need engineers who can make that foundation (Kubernetes, storage, networking, deployments) fast, reliable, and cheap at web scale. You'll own real infrastructure from day one, not tickets in a backlog.
Equity Range: Competitive equity. Details shared during the process.
Job Type: Full-Time
Experience: 5+ years in DevOps, Platform Engineering, or Cloud Infrastructure
Work Authorization: Must be authorized to work in the United States or Canada. We're not able to sponsor US visas right now. For Canada, we'll consider sponsorship on a case-by-case basis through our Toronto Hub.
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...
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