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 @ 7
AWS @ 6
Azure @ 6
BI @ 4
Communication @ 6
Data Engineering @ 4
Databricks @ 4
Experimentation @ 7
GenAI
Generative AI @ 4
Grafana @ 7
LLM
Looker @ 4
Observability @ 4
Power BI @ 4
Slack
Snowflake @ 4
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 is looking for an AI Software Engineer with a strong software engineering background, a quick-iteration mindset, and a passion for experimentation. The role focuses on shipping and scaling AI-powered features that help users understand and act on large enterprise datasets. You will work within the autonomous 2nd Horizon skunkworks initiative, developing analytics-focused AI agents and information-retrieval capabilities for use cases such as product analytics and sales data.
This is a remote position. Candidates are being considered in Germany, Ireland, Sweden, Spain, and the United Kingdom only.
Responsibilities
- Build and deliver high-performance AI features that help users discover, organize, and optimize access to large datasets.
- Prototype, test, validate, ship, and iterate on LLM- and agent-powered workflows for the data engineering lifecycle.
- Develop AI-driven product features, including agentic integrations with internal tools such as Slack and alerting systems.
- Engage with internal data teams for dogfooding and user feedback.
- Use AI and automation tools to improve product functionality and development workflows.
- Design, develop, test, and ship scalable and maintainable AI solutions.
- Take ownership of solutions from initial concept through production delivery and ongoing improvement.
- Communicate effectively and contribute across teams in a dynamic, collaborative environment.
Requirements
- Experience with large language models, context engineering, and applications powered by generative AI.
- A proven track record of delivering production-grade software that is actively used by customers or users.
- Strong software engineering skills and experience building user-facing systems.
- Exposure to cloud-native environments such as AWS, Google Cloud Platform, or Microsoft Azure.
- Experience using observability tools to understand and troubleshoot system behavior.
- Ability to work independently, handle ambiguity, define scope, and drive projects forward.
- Effective communication and a collaborative, solutions-oriented approach.
Bonus Points
- Experience with agent frameworks or multi-agent workflows.
- Experience as a data analyst or working with data platforms such as Looker, Tableau, Power BI, Snowflake, or Databricks.
- Experience building tools for data engineering.
Benefits
- Base compensation in Spain of €94,000–€117,000 per year.
- Equity, bonus where applicable, and other benefits.
- 100% remote work and a global culture.
- In-person onboarding.
- 30 days of annual leave per year, including three Grafana Shutdown Days, subject to local legislation.
- Career growth opportunities, transparent communication, and an open-source, innovation-driven culture.
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