Staff Software Engineer - Databases, Tempo | United Kingdom | Remote

Grafana Labs Grafana Labs · Data AI · Germany, Ireland, Spain, Sweden, United Kingdom · Remote · R&D : Databases

Staff Software Engineer role focused on building and scaling Tempo, an open-source distributed tracing backend for Grafana. The role involves technical leadership, architecture ownership, API design for humans and agents, operational excellence, and contributing to open source. While the role itself is not directly building AI models, it is evolving the core observability platform to support AI-driven assistants and LLM-friendly interfaces, making it a key component in an AI-powered observability stack.

What you'd actually do

  1. Lead multi-quarter technical initiatives from problem framing through rollout, e.g., trace aggregation APIs, Limitless Tempo, autoscaling cells and customer limits, or query engine improvements.
  2. Own the architecture of core Tempo components: ingestion, storage, query, and metrics generation. Drive design reviews, make sharp trade-offs on performance, cost, and complexity, and document the “why” for the team.
  3. Design APIs for humans and agents. Shape the next generation of Tempo’s interfaces (structured, deterministic, discoverable) so that Act 3 products, LLM-driven assistants, and external integrators can build on Tempo reliably.
  4. Drive operational excellence. Own outcomes against concrete SLOs (P99 write latency, incident recurrence, TCO per ingested GB) and push the team toward Zero Ops through automation, parameterized rollouts, and actionable alerts.
  5. Partner with Product and sibling teams. Work closely with PMs and with App Observability, Asserts, Drilldown, and Grafana Assistant teams to understand how Tempo gets consumed and to ship what unblocks them.

Skills

Required

  • Distributed systems design
  • High-throughput data ingestion
  • Scalable storage systems
  • Query engine optimization
  • API design
  • Operational excellence
  • SLO ownership
  • Automation
  • Open source contribution
  • Technical leadership

Nice to have

  • Observability platforms
  • Tracing systems
  • LLM integration
  • Agentic workflows

What the JD emphasized

  • evolving Tempo from a SaaS database into a platform that powers Grafana’s next generation of observability products (App Observability, Asserts, Traces Drilldown, and AI-driven assistants)
  • evolve Tempo into a platform enabler: higher-density APIs, trace aggregation, TraceQL metrics math, and machine/LLM-friendly interfaces that downstream products and agents can build on.
  • Prepare Tempo for an agent-driven world: larger, burstier, higher-cardinality workloads, and new categories of AI-powered workflows, such as assistant-driven triage and “why is this slow?”- style investigations.
  • Design APIs for humans and agents.
  • Shape the next generation of Tempo’s interfaces (structured, deterministic, discoverable) so that Act 3 products, LLM-driven assistants, and external integrators can build on Tempo reliably.
  • Trace aggregation and higher-density APIs: extend TraceQL metrics, design LLM-friendly response types, and make Tempo a first-class data source for Grafana’s AI assistant.