Cloud DevOps Engineer
- Market p25–p75
- $200k–$300k
- Opened · 30d
- +0
- Closed · 30d
- −0
- Opened · 7d
- +2167% of open
- All devops / sre / infra
- 7,027open
Cloud DevOps Engineer
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.
Salary: $246,000–$271,000 USD/year (SF) / $204,000–$212,000 CAD/year (Toronto)
Equity Range: Competitive equity. Details shared during the process.
Location: San Francisco, CA (SF HQ) or Toronto, ON (Toronto Hub). Hybrid, onsite 3+ days a week.
Job Type: Full-Time
Experience: 5+ years in DevOps, Platform Engineering, or Cloud Infrastructure
Work Authorization: Open to candidates already authorized to work in the US or Canada. 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. For Canada, we’ll consider work permit sponsorship case by case through our Toronto Hub.
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.
Our Values
Bias to action: We move fast, ship hard, and don’t wait to be told.
Realistic about AI: We’re clear-eyed about what AI can and can’t do, and we keep pushing to use it where it actually works.
All in: The next few years matter a lot, and we’re all in for them.
Human connection: As intelligence gets cheaper, relationships with customers, partners, and each other matter more.
What You'll Do
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
Own CI/CD, Infrastructure as Code, automations, and containerized deployments across the platform
Drive down infrastructure cost per request while traffic and data volume grow
Build the observability that keeps latency, throughput, and reliability predictable, and define the SLIs, SLOs, and customer-facing SLAs we hold ourselves to
Build and support our enterprise controls: SSO/SAML, RBAC, audit logging, tenant isolation, private networking, and the infrastructure behind SOC 2 and customer security reviews
Work directly with product and search engineers to productionize new services, retrieval, and ML workloads
Own the incident lifecycle with engineers, from on-call and triage process to postmortems and resolution
What We'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