Staff Backend Engineer

Role Overview

Join Grafana Labs as a Staff Backend Engineer in the Adaptive Telemetry group. You will set technical direction, lead cross-functional initiatives, and own architecture, reliability, performance, and cost for critical backend systems—helping to improve observability and automation.

Responsibilities

• Drive technical strategy and roadmap; define the architectural vision and influence product/engineering decisions.
• Lead end-to-end delivery of large, cross-functional projects (planning, design, execution, rollout, and long-term operations).
• Own architecture, reliability, performance, and cost for critical systems, making pragmatic tradeoffs across scalability, availability, latency, and cost.
• Define and manage SLOs/SLIs, perform capacity planning, tune performance, and drive reliability improvements end-to-end.
• Improve observability and automation, and represent engineering both internally and externally.
• Align stakeholders and mentor engineering talent in a remote-first environment.

Requirements

• Strong coding and design skills; ability to lead technical designs and write clear, maintainable, well-tested code.
• Proficiency with backend development: Go is used (experience with Python/C/C++/Rust or similar translates).
• Customer-focused, proactive, and comfortable acting with a bias toward action.
• Proven ownership of reliability and performance, including experience defining SLOs/SLIs, capacity planning, and tuning.
• Ability to influence without authority, align cross-functional stakeholders, and drive outcomes remotely.
• Strong written and verbal communication across technical and non-technical stakeholders.
• Hands-on cloud and platform experience with cloud-native architectures (microservices, containers/Kubernetes, and IaC) and operational practices.
• Demonstrated delivery of large distributed systems spanning multiple teams with evidence of technical leadership.
• Deep systems-design understanding of tradeoffs (latency, consistency, availability, scaling, and cost).
• Comfort with AI-assisted development and integrating AI-powered developer tools into workflows.
• Experience with messaging/telemetry and observability tooling; familiarity with Kafka and Prometheus/Grafana (or equivalents).

Nice to Have

• Practical experience using AI-powered developer tools within engineering workflows.