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Salary: EUR 104,000 - 130,000 / annual
Grafana Labs is building an AI-native data intelligence system as part of a new skunkworks initiative to bring observability to the broader business. The goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data across the enterprise. This system provides agents reliable, governed access to enterprise context including data retrieval, metadata, definitions, lineage, quality signals, and institutional knowledge.
You will join a new, high-autonomy team of seasoned Grafanistas and new hires operating with significant ownership and empowerment. Engineers make decisions, move quickly, and validate ideas early within a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership.
As Senior Backend Engineer focused on Databases, you will take ownership of building the underlying storage system for the general-purpose data platform. The database layer supports both OLAP and OTLP capabilities for classic analytics queries while serving freshly stored data. It embraces separation of compute and storage and is designed to run on multiple cloud providers.
Key responsibilities include:
- Design, implement, test, and operate database components: ingestion, query planning, distributed query execution, data formats, and storage formats
- Build scalable SaaS foundations including multi-tenant architecture, tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries
- Create APIs and database interfaces enabling 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 as the project moves from prototype to production
- Instrument database services with metrics, logs, traces, alerts, and dashboards; use observability tools to understand system behavior and improve reliability
- Shape technical direction for architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices
- Communicate effectively in a dynamic, collaborative environment and contribute across teams
- Take full ownership of database solutions ensuring they are innovative, scalable, maintainable, and aligned with real user workflows
This is an early-stage role with high autonomy. You should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that evolve from internal dogfooding to production-grade SaaS. As the team matures, there is broad opportunity to expand or redefine the role based on impact and initiative.
Grafana Labs is a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Customers include Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce.
REQUIREMENTS:
- Strong engineering skills: solid experience building production-grade, user-facing software systems; self-starter capable of tackling complex engineering problems and making design decisions with minimal supervision
- AI experience with practical mindset: familiar with AI technologies and frameworks, focused on delivering high-quality solutions that work in the real world
- Quick iteration and experimentation: comfortable releasing prototypes, collecting feedback, and iterating pragmatically
- Proven initiative: take ownership and drive projects forward; can deal with ambiguity and define scope where loosely defined
- 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 such as Go, C++, or Rust
- Proven track record of delivering software that made it into production and 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
