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Salary: EUR 97,000 - 121,000 / annual
Grafana Labs is building an AI-native data intelligence system as part of a new skunkworks initiative to bring observability to enterprise data. The company operates a fully managed observability platform trusted by over 10,000 organizations including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce. This is a remote-first, 100% distributed company with team members across 40+ countries.
You will join a high-autonomy team building the underlying storage system for a general-purpose data platform. The database layer supports both OLAP and OTLP capabilities, embraces separation of compute and storage, and is designed to run on multiple cloud providers. This is an early-stage role where you'll work through ambiguity, make pragmatic architectural decisions, and build systems that evolve from internal dogfooding to production-grade SaaS.
Key responsibilities include:
- Take ownership of database components: design, implement, test, and operate ingestion, query planning, distributed query execution, data formats, and storage formats
- Create a scalable SaaS foundation with multi-tenant architecture, tenant isolation, usage tracking, quotas, audit logs, and reliable service boundaries
- Build APIs and database interfaces for AI agents, MCP tools, CLIs, and internal applications to retrieve data quickly
- Partner across product and infrastructure teams to balance fast experimentation with long-term reliability
- Instrument database services with metrics, logs, traces, alerts, and dashboards; use observability tools to understand system behavior
- Contribute to technical direction: shape architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices
- Communicate effectively in a dynamic, collaborative environment and take full ownership of database solutions
The team operates with transparency, autonomy, and trust. Engineers are empowered to make decisions and move quickly while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership.
REQUIREMENTS:
- Strong engineering skills: solid experience building production-grade, user-facing software systems; self-starter capable of tackling complex engineering problems with minimal supervision
- AI experience with practical mindset: familiar with AI technologies and frameworks, focused on delivering high-quality real-world solutions
- Quick iteration and experimentation: comfortable releasing prototypes, collecting feedback, and iterating pragmatically
- Proven initiative: take ownership and drive projects forward, push boundaries for impactful solutions, deal with ambiguity and define scope
- Collaborative attitude: communicate effectively with peers, open to feedback, solutions-oriented mindset
- Experience with distributed systems, catalogs, table formats, and query engines
- Mastery of a programming language like Go, C++, or Rust
- Proven track record of delivering software into production that is actively used by users
- Exposure to cloud-native environments (AWS, GCP, Azure)
- Experience using observability tools to understand and troubleshoot system behavior
BONUS:
- Experience building distributed query engines
- Experience building data warehouses and/or data lakes
- Experience building tools for data engineering
