Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
API @ 4
Communication @ 6
Go @ 7
Grafana @ 4
Kubernetes @ 4
LLM @ 4
Observability @ 4
OpenTelemetry @ 4
Parquet @ 4
Prometheus @ 4
Rust @ 7
SQL @ 4
Security
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Grafana Labs is seeking a Staff Software Engineer to help build and operate Tempo, the open-source distributed tracing backend behind Grafana Cloud Traces and Grafana Enterprise Traces. Tempo supports trace search, span-derived metrics, and connections between tracing data, logs, metrics, and profiles across the Grafana stack.
This role will focus on evolving Tempo from a SaaS database into a platform for Grafana's next generation of observability products, including App Observability, Asserts, Traces Drilldown, and AI-driven assistants. Key priorities include operational excellence, autoscaling, higher-density APIs, TraceQL metrics, improved query performance, multi-cell operations, and support for bursty, high-cardinality AI-driven workloads.
Responsibilities
- Lead multi-quarter technical initiatives from problem framing through rollout, such as trace aggregation APIs, Limitless Tempo, autoscaling cells, customer limits, and query engine improvements.
- Own the architecture of core Tempo components, including ingestion, storage, querying, and metrics generation.
- Drive design reviews and make trade-offs involving performance, cost, and complexity.
- Design structured, deterministic, discoverable APIs for human users, AI agents, downstream products, and external integrators.
- Drive operational excellence against SLOs such as P99 write latency, incident recurrence, and total cost of ownership per ingested gigabyte.
- Improve automation, parameterized rollouts, actionable alerts, and Zero Ops practices.
- Partner with Product and sibling teams, including App Observability, Asserts, Drilldown, and Grafana Assistant.
- Mentor engineers through code reviews, design feedback, pairing, and technical writing.
- Participate in on-call for services developed by the team and contribute to incident response and post-incident learning.
- Contribute to the Tempo open-source project, review external contributions, and engage with the community.
- Use AI coding assistants for prototyping, test generation, refactoring, documentation, and incident follow-ups within security guidelines.
Example projects include trace aggregation and higher-density APIs, end-to-end autoscaling, agent-scale ingestion and querying, query performance improvements, multi-cell rollout tooling, and customer-facing limits and self-service capabilities.
Requirements
- Track record of leading complex, multi-quarter initiatives spanning design, delivery, and operations.
- Substantial hands-on experience building and operating distributed data systems in production, such as ingestion pipelines, storage engines, or query execution systems.
- Strong software craftsmanship, including the ability to write clean, robust, performant, and maintainable software.
- Strong experience with Go, or deep experience in systems languages such as Rust, C, or C++ with a path to Go.
- Experience owning production services, participating in on-call rotations, reducing operational toil, and working with SLOs.
- Customer-focused and pragmatic approach to analyzing, designing, delivering MVPs, learning, and iterating.
- Ability to lead through design documents, reviews, and shipped code rather than hierarchy.
- Clear communication skills for a fully remote, asynchronous environment.
Bonus Qualifications
- Experience with tracing, OpenTelemetry, or large-scale observability systems.
- Experience designing query languages, SQL- or TraceQL-like engines, or programmatic APIs.
- Experience with columnar storage formats such as Parquet or purpose-built on-disk formats for analytical workloads.
- Experience operating multi-tenant, multi-cell SaaS infrastructure at scale on Kubernetes.
- Experience building structured APIs, metadata or discovery endpoints, deterministic outputs, or evaluation harnesses for AI and LLM consumers.
- Open-source contribution or maintainership experience.
- Experience using Grafana, Prometheus, Loki, or Tempo on call or in a homelab.
- Experience working in a fully remote, globally distributed team.
Benefits
- Equity, bonus where applicable, and other company benefits.
- 100% remote, globally distributed work environment.
- Company-funded usage budget for modern AI coding assistants.
- In-person onboarding.
- Global annual leave policy of 30 days per year, including 3 Grafana Shutdown Days, subject to local legislation.
- Career growth pathways, transparent communication, empowered teams, and a high-trust culture.
The role is remote, with applicants considered from Spain, Sweden, the United Kingdom, Ireland, or Germany. Grafana Labs is an equal opportunities employer.