Staff Software Engineer, Grafana Labs

• 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
• Strong programming background in a modern language (Python and Go are primary, but prior experience is not required)
• Experience designing, building, and operating large-scale distributed systems
• Strong experience with SRE practices, including operating and evolving production systems at scale
• Strong understanding of reliability engineering concepts (e.g. incident management, observability, and failure modes)
• Strong experience of defining or applying SLIs/SLOs, error budgets, or reliability metrics
• Experience with test automation, including performance and functional testing
• Ability to influence engineering practices through clear technical communication, reviews, and collaboration
• Strong interpersonal skills and ability to work effectively across teams
• Familiarity with modern software engineering processes and delivery practices
• Self-driven and comfortable operating with a high degree of autonomy and ambiguity
• Experience participating in blameless incident response and writing high-quality post-incident reviews

Desirable

• We are the team behind Grafana k6, Grafana Cloud k6, and Grafana Cloud Synthetics, used by teams globally to ensure resilient, high-performing systems
• This opportunity is with the Grafana Cloud k6 squad, who build and operate our performance testing product
• Grafana Cloud k6 is built around the OSS k6 and targeted at users looking to run performance tests at scale
• Our enterprise and SaaS offerings allow customers to load test their systems by running distributed tests from 15+ regions worldwide, using hundreds of thousands of virtual users sending millions of requests per second
• We ingest huge volumes of data generated by k6, which can be used to view, correlate and analyze metrics from each test
• K6 is a product used by other engineers, and as such, we are looking for people enthusiastic about building high-quality tools they would want to use themselves
• Due to our small teams and fast development pace, you will have a substantial and immediate impact on how the end product is architected, developed, and how the engineering team operates
• Your role will focus on establishing and scaling a cross-team culture of engineering excellence by setting standards and guiding adoption of strong engineering practices that improve reliability and operational ownership
• As this foundation matures, the role is expected to expand into broader application and product development leadership, contributing architectural and technical depth beyond operational excellence
• Contribute hands-on to the codebase by designing and implementing production-quality software
• Guide teams in the design, development, evolution, and operation of large-scale, distributed cloud systems
• Build and scale a strong culture of operational excellence by defining standards and coaching teams to own reliability and availability
• Help mature SRE practices, including incident response and PIRs, on-call readiness, runbooks, alerting, observability, and release/change management
• Establish reliability frameworks such as SLIs/SLOs and error budgets, and use them to guide prioritization and engineering trade-offs
• Provide visibility into system health through clear operational metrics and reliability reporting
• Participate in the on-call rotation as a primary escalation point and contribute to incident resolution
• Influence product and system direction through design reviews, architectural discussions, and cross-team collaboration
• Share knowledge through clear, high-quality documentation and technical communication—internally and, where appropriate, externally—to help teams build and operate systems more effectively
• As the reliability foundation matures, grow into broader application and product development leadership, contributing architectural and technical depth beyond operations
• 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 paired with strong code review and quality standards
• You’ll also have access to frontier models (e.g., GPT-Codex 5/3, Claude Opus 4.6, Gemini 3 Pro)