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As a Staff Backend Engineer, you'll develop and maintain scalable reconciliation systems within Grafana Cloud, enhancing reliability and operational efficiency while collaborating with multiple teams.

Design practical, scalable user experiences for Grafana's Incident Response & Management products across web, mobile, integrations and agentic workflows. Collaborate with product, engineering, research, and customers, run research, document needs and trade-offs, and mentor other designers to evolve the product and design practice in a fully remote environment.

Own and run customer lifecycle demand-generation programs to drive expansion, cross-sell, and adoption across email, in-app, web, paid, events, and outbound. Build AI-driven, agentic workflows to automate execution, align programs with sales motions, instrument pipeline impact, and partner with sales and customer teams to optimize coverage and results.

Lead technical pre-sales engagements for Grafana Cloud: deliver demos, evaluations, and enablement; partner with Sales to qualify and close opportunities; communicate customer feedback to Product and Engineering; create documentation and enablement content; drive technical conversations and competitive positioning.

Design, build, and operate core backend services for an AI-native context management system: ingestion, indexing, retrieval APIs, multi-tenant SaaS features, and agent-facing integrations. Define architecture, ensure observability, iterate from prototype to production, and collaborate across product and infrastructure while owning service reliability and technical direction.

Build and scale Grafana Labs' internal engineering platform: design, ship, and operate cloud-native, distributed systems; reduce region build timelines; own reliability, performance, capacity planning, SLOs/SLIs, and on-call duties; collaborate cross-functionally and take projects from design to production.

Lead architecture and delivery of large, distributed telemetry database systems for Grafana Cloud. Own reliability, performance, cost, SLOs/SLIs, incident response, observability, automation, and cross-team alignment while mentoring engineers and driving technical strategy.

Support Grafana's AI organization by defining KPIs, designing experiments, guiding instrumentation, building dbt models, creating dashboards, and translating analytics into product recommendations to improve AI-powered features and workflows.

Lead marketing analytics as the architect of the data-driven growth engine: build BigQuery data schemas, predictive models (attribution, MMM, LTV), agentic AI monitoring, automated orchestration, executive BI, and target-setting frameworks to optimize demand generation and funnel quality across GTM.

The role involves leading AI-driven nurture programs, executing multi-channel campaigns, and analyzing data to enhance demand generation for Grafana Labs.