Jobs at Grafana Labs

Join the k6 core team to develop and maintain k6, a Go-based performance testing tool. Design and implement features, ensure production-quality code, work on distributed test execution services, collaborate on design and code reviews, and support the open-source project while focusing on correctness, scalability, and developer experience.

Develop and maintain full-stack integrations for Grafana Cloud observability: build TypeScript/React frontends, Go backends, and Jsonnet mixins. Ship end-to-end features, own projects from design to production, contribute upstream to Prometheus/OpenTelemetry, participate in on-call rotation, and represent the team's work across the org.

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 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.

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.

Design, prototype, and ship production AI/ML features that analyze observability data to detect, triage, and resolve incidents. Rapidly iterate on LLM- and agent-powered workflows, collaborate cross-functionally, integrate AI with internal tools and alerting systems, and ensure solutions are scalable, maintainable, and aligned with user workflows.

The role involves designing and delivering integrations across the GTM stack, developing internal tools, and leading technical architecture in a collaborative setting.

As a Senior Product Manager for Infrastructure Observability at Grafana Labs, you will define product vision and strategy, manage the product roadmap, and facilitate communication between engineering, design, and go-to-market teams. You will focus on customer needs and drive adoption across teams to improve product experiences.

As a Staff Backend Engineer at Grafana Labs, you'll lead technical initiatives for Tempo's development, ensuring operational excellence and integrating with other products while mentoring engineers and contributing to open source.

In this role, you will lead the web development team, manage the technical execution of Grafana's website, drive AI integrations, and enhance user experience while collaborating with various stakeholders.

Design, build, and operate production multi-agent AI systems and automation for Marketing Operations. Integrate LLMs with business systems (BigQuery, CRMs, Slack), implement RAG pipelines, observability, governance, and scalable serverless/containerized services. Partner with GTM teams to deliver measurable automation and self-service tooling.

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.

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.

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.