Staff AI Engineer - 2nd Horizon | Sweden | Remote

Grafana Labs Grafana Labs · Data AI · EMEA · R&D: Second Horizon

Grafana Labs is seeking an AI Software Engineer for their '2nd Horizon' skunkworks initiative. The role focuses on building AI-powered features and AI agents to help users understand and act on enterprise data, with a specific emphasis on product analytics and sales data. The engineer will be responsible for designing, developing, testing, and shipping LLM- or agent-powered workflows, integrating them with internal tools, and ensuring scalability and maintainability. The position requires strong software engineering skills, experience with LLMs and GenAI applications, and a practical, iterative approach to shipping production-ready AI solutions.

What you'd actually do

  1. Build and deliver AI solutions: Take ownership of developing delightful, high-performance AI features to help users discover, organize, and optimize access to large datasets.
  2. Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for the data engineering lifecycle.
  3. Collaborate: Work with the rest of the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems while engaging with internal data teams for dogfooding.
  4. Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows.
  5. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

Skills

Required

  • Experience with LLMs, context 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.
  • Strong engineering skills
  • AI experience with a practical mindset
  • Quick iteration and experimentation
  • Proven initiative
  • Collaborative attitude

Nice to have

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What the JD emphasized

  • shipping and scaling impactful features
  • shipping and evolving LLM- or agent-powered workflows
  • Proven track record of delivering software that made it into production and is actively used by users

Other signals

  • AI-driven features
  • AI agents
  • LLM-powered workflows
  • information retrieval