$ cat jobs/software-engineer-platform-productivity-united-kingdom-remot-grafana-labs-63e72c56da1d.json
Software Engineer - Platform Productivity | United Kingdom | Remote
Grafana Labs , the company behind the open observability cloud, is founded on the principles of open source, open standards, open ecosystems, and open culture. Grafana Cloud, our fully managed observability platform, is flexible and built for scale. With Grafana Cloud's actually useful AI, organizations can see, understand, and act on all their disparate data to move at the speed of their ambitions. Today, more than 35 million users and 7,000+ customers – including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce – trust Grafana Labs to ensure reliability of their applications and systems, resolve incidents quickly, and optimize their telemetry to reduce noise and cost. We are a 100% remote company with 1,600+ team members across 40+ countries, and we’re backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at and follow us on LinkedIn and X. We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we would be interested in applicants living in UK time zones only at this time. Software Engineer - Platform Productivity The Opportunity: Grafana Cloud moves millions of metrics, log lines, and traces per second from our customers' environments into a highly available, low-latency stack that processes and stores these data, and serves them to dashboards and alerting tools. We aim to grow this to hundreds of millions per second, and it's critical that as we grow, we improve our performance, increase our reliability, and, of course, do it efficiently and effectiv
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