Software Engineer

Born in Bilbao, growing everywhere. Zenrows is one of Europe's fastest-growing startups, and we've been fully remote since day one. We build the infrastructure that lets thousands of companies, in e-commerce, finance, real estate, and AI, extract data from the web reliably and at scale. Our stack isn't a CRUD app. We orchestrate thousands of CPU cores, handle hundreds of millions of requests per day, push terabytes of outbound traffic monthly, and simulate human behavior to stay ahead of the most advanced anti-bot systems on the market. The engineering problems here are real, and your work will be visible in production within weeks. The Role You will own critical infrastructure components that ingest, enrich, and route billions of data points — ensuring performance, reliability, and horizontal scalability. Your work will directly impact throughput, customer SLAs, billing accuracy, and platform reliability. As our Staff Software Engineer, you'll operate at the intersection of deep system design, hands-on implementation, and technical leadership. You’ll collaborate with other engineers to design fault-tolerant, observable, and cost-efficient systems that support our distributed workloads. We’re a remote-first company with a fast-paced, high-impact culture. In this role, you’ll work closely with our CEO, Aurken, and our Director of Engineering, Alina. What You'll Work On Scraping Platform Reliability & Scale - Own the availability and success rate of the scraping API — the core product metric - Drive architectural improvements that increase throughput and reduce failure rates across diverse target sites - Design systems that degrade gracefully, self-heal, and adapt to shifting detection patterns without human intervention Distributed Job Execution - Design and evolve the async execution architecture that processes millions of concurrent tasks across nodes and regions - Build robust retry strategies, idempotency, dynamic routing, rate limiting, and prioritization - Own scheduling infrastructure for recurring, event-driven, and user-triggered workflows Reliability & Observability - Define and enforce SLAs for both the scraping API and job processing systems - Build alerting and dashboards for failure modes, success rate regressions, throughput anomalies, and retry storms - Lead incident response and post-mortems; participate in on-call responsibilities for the systems you own Technical Leadership - Contribute meaningfully to architecture decisions — not just implementation - Raise the bar in design reviews and engineering standards across the team - Mentor peers and drive adoption of sound distributed systems practices What We're Looking For Required - 10+ years of backend engineering experience, with meaningful time spent building and operating high-throughput, high-availability distributed systems - Strong fundamentals in concurrency, fault tolerance, consistency models, and systems design - Hands-on experience with queueing and messaging systems (SQS, Kafka, RabbitMQ, Pub/Sub, BullMQ, or similar) - Comfortable operating at scale — tens of millions of requests or events per day, across multiple nodes or regions - Solid production instincts: you think about retries, deduplication, backpressure, and observability before writing the first line - Clean, maintainable code in Go (or a comparable backend language) - Experience with distributed tracing, metrics, and logging (OpenTelemetry, Prometheus, Grafana, or equivalent) - Clear communicator — you can drive a technical debate and explain complex tradeoffs to non-engineers alike Bonus - Experience with browser automation at scale (Playwright, Puppeteer, or similar) - Familiarity with proxy infrastructure, TLS fingerprinting, or HTTP-level anti-bot patterns - You've designed or operated a workflow engine, job scheduler, or orchestration system - You have a war story from a system that broke badly in production — and clear lessons learned from it - Multi-cloud deployment experience What Makes This Different - Full ownership. You'll own systems end-to-end — design, deployment, and operations. - Direct impact. The systems you build directly affect customer SLAs, billing accuracy, and the core product success rate. - No layers. You'll work closely with our CEO and Director of Engineering. - No methodology theater. We skip the ceremony and give you a horizontal view of the problem.