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Software Engineer - Synthetic Monitoring | UK | Remote
Grafana LabsWebsite
Full-time
Mid Level
Remote
Europe
Posted Yesterday1 views
Job Description
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 grafana.com 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 located in Spain, Sweden, UK, Ireland or Germany.
Software Engineer - Synthetic Monitoring
The Opportunity:
The Synthetic Monitoring squad builds and operates Grafana Cloud Synthetic Monitoring, used by teams globally to proactively verify that their critical user journeys, APIs, and services work as expected - before their customers notice they don't.
Synthetic Monitoring is a multi-tenant distributed system implemented in Go, running on Kubernetes across all major cloud providers (AWS, GCP, Azure), executing billions of synthetic tests each month from probe locations around the world and from customer-operated private probes.
The product is in a scale phase, and our focus is on making Synthetic Monitoring a deeply integrated part of Grafana Cloud: connecting checks to real user experience and cross-product investigation workflows, making check results a trusted signal for AI-assisted workflows, and enabling large organizations to operate the product at enterprise scale on our infrastructure and on their own private probes.
The role is full-stack in the real sense: the same engineer who designs how a check execution flows through scheduling, probes, and the telemetry pipeline should also be able to build the workflow that lets a user understand and act on the result.
As a company we are remote-first and global, we embrace people of different experiences and backgrounds to build diverse teams where every person brings a new perspective to the software. We are looking for Software Engineers who are passionate about building reliable systems and providing seamless experiences for our customers to join our growing team! Our stack is Golang, Typescript and React, but we build tools for people using many other stacks.
What you'll be doing:
As a Software Engineer on the Synthetic Monitoring squad, you will work across the whole system - Go services and agents on the backend, a TypeScript/React application on the frontend and you'll be expected to reason about it as one system, not two halves. Specifically, you will:
• Own features end-to-end across the stack: from API and data model design in Go, through the execution pipeline, to the user-facing workflows in TypeScript/React
• Design and evolve systems, not just features: contribute to architectural decisions on scheduling, probe lifecycle, telemetry ingestion, and API design that shape how the product scales
• Build the cross-product and AI-assisted workflows that connect Synthetic Monitoring to the wider Grafana Cloud platform
• Make the product operable at enterprise scale: the governance and organization primitives that let teams with hundreds of checks manage Synthetic Monitoring as code and with confidence
• Break down complex, ambiguous problems into incremental deliverables and iterate quickly based on feedback
• Ensure quality through testing, observability of your own systems, and documentation: our checks are something customers alert on, so reliability is a feature
• Be a part of the team's on-call rotation and take ownership of the services you're running
We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always with strong code review and quality standards. You'll also have access to the latest frontier models from OpenAI, Anthropic, and Google.
Technologies you'll work with:
• Go (backend services, APIs, and the synthetic monitoring agent)
• TypeScript / React (the Synthetic Monitoring app in Grafana)
• Kubernetes across AWS, GCP, and Azure
• k6 (the execution engine behind scripted and browser checks)
• Grafana ecosystem (Mimir, Loki, Prometheus)
What Makes You a Great Fit:
• You are comfortable working in a remote-first company; communication is key.
• For us, working together means being collaborative, friendly, kind, and respectful. We operate by consensus. You can contribute to a discussion, disagree constructively, and commit to the team's decision. You are able to communicate design decisions clearly in written and spoken English.
• Strong Go, or a path to it. We build Synthetic Monitoring in Go. Deep experience building and operating production backend systems in another systems…
AI Stack
Skills Required
RAG
Fullstack + AI
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