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
AWS
Audit
Azure
Data Engineering @ 4
Databricks @ 4
Experimentation
GCP
GenAI @ 4
Grafana @ 4
LLM
Looker @ 4
Observability @ 4
Prompt Engineering @ 4
Snowflake @ 4
System Administration
Tableau @ 4
- 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, the company behind the open observability cloud, is founded on the principles of open source, open standards, open ecosystems, and open culture. Grafana Cloud, our fully managed observability platform, is flexible and built for scale.
We are a 100% remote company with 1,600+ team members across 40+ countries.
This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany.
The Opportunity
At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business.
Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context.
We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system.
What You'll Be Doing
- Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration.
- Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
- Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings.
- Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production.
- Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability.
- Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area.
- Effective communication: Work in a highly dynamic and collaborative environment.
- Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are innovative but also scalable, maintainable, and aligned with real user workflows.
What Makes You a Great Fit
- Strong engineering skills: Solid experience building production-grade, user-facing software systems. Self-starter; capable of tackling complex engineering problems.
- AI experience with a practical mindset: Familiar with AI technologies and frameworks; focus 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: Ownership of projects; can deal with ambiguity and define scope where things are loosely defined.
- Collaborative attitude: Communicate effectively; open to feedback; solutions-oriented.
Requirements
- Experience with LLMs, prompt engineering, and building applications powered by GenAI.
- Proven track record of delivering software that made it into production and is actively used by users.
- Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure).
- Experience using observability tools to understand and troubleshoot system behavior.
Bonus Points for
- Experience building or working with agent frameworks or multi‑agent workflows.
- Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks).
- Experience building tools for data engineering.
How we work
We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing.
Compensation & Rewards
In Sweden, the Base compensation range for this role is SEK 878,578 - SEK 1,054,294. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process.
Benefits include equity, bonus (if applicable) and other benefits listed here.