Staff Backend Engineer - Grafana Second Horizon | UK | Remote

📍 Germany
📍 Spain
📍 United Kingdom
📍 Ireland
📍 Sweden
GBP 104,000-124,800 per year
SENIOR
✅ Remote

Tech Stack

AI @ 4 API AWS @ 4 Audit Azure @ 4 BI @ 4 Communication @ 7 Data Engineering @ 4 Databricks @ 4 Experimentation GCP @ 4 GenAI Generative AI @ 4 Grafana @ 4 LLM Looker @ 4 Observability @ 4 Power BI @ 4 Prompt Engineering @ 4 Snowflake @ 4 System Administration Tableau @ 4

Details

Grafana Labs is building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context, including data, metadata, definitions, lineage, quality signals, and institutional knowledge. The team is developing the first production services for this context layer management system.

This Staff-level Backend Engineer role will design and ship the backend architecture for ingestion, context storage, retrieval APIs, and agent-facing integrations. The role involves working in an early-stage, high-autonomy environment and making pragmatic architectural decisions as the system evolves from internal dogfooding to production-grade SaaS.

Responsibilities

  • Design, implement, test, and operate backend services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration.
  • Help define and build a scalable, multi-tenant SaaS architecture, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
  • Build APIs and service interfaces that enable AI agents, MCP tools, CLIs, and internal applications to retrieve context, provenance, confidence signals, and warnings.
  • Partner across product and infrastructure to balance rapid experimentation with long-term reliability.
  • Instrument services with metrics, logs, traces, alerts, and dashboards, and use observability tools to understand system behavior and improve reliability.
  • Contribute to architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area.
  • Communicate effectively and contribute across teams in a dynamic, collaborative environment.
  • Take ownership of AI solutions and ensure they are scalable, maintainable, and aligned with real user workflows.

Requirements

  • Strong experience building production-grade, user-facing software systems.
  • Ability to tackle complex engineering problems, make decisions with minimal supervision, and work effectively in an ambiguous early-stage environment.
  • Familiarity with AI technologies and frameworks, with a practical focus on delivering high-quality solutions.
  • Experience with LLMs, prompt engineering, and building applications powered by generative AI.
  • Proven track record of delivering software that reached production and is actively used by customers or users.
  • Experience working in cloud-native environments such as AWS, GCP, or Azure.
  • Experience using observability tools to understand and troubleshoot system behavior.
  • Ability to prototype, collect feedback, iterate quickly, and define scope where requirements are loosely defined.
  • Strong communication, collaboration, ownership, and initiative.

Bonus Points

  • Experience building or working with agent frameworks or multi-agent workflows.
  • Experience as a data analyst or with data platforms such as Looker, Tableau, Power BI, Snowflake, or Databricks.
  • Experience building tools for data engineering.

Work Environment

Grafana Labs is a remote-first, 100% remote company. The team meets regularly over video and works primarily asynchronously and in writing. The role is open to applicants located in Spain, Sweden, the United Kingdom, Ireland, or Germany.

Compensation & Benefits

  • United Kingdom base compensation: GBP 103,958–GBP 124,750 per year.
  • Equity, bonus where applicable, and additional benefits.
  • Global annual leave policy of 30 days per year, including three Grafana Shutdown Days, subject to local legislation.
  • In-person onboarding.
  • Career growth pathways, transparent communication, empowered teams, and a global collaborative culture.

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