Remote Staff AI Engineer - 2nd Horizon | UK | Remote in York

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. With Grafana Cloud's actually useful AI, organizations can see, understand, and act on all their disparate data to move at the speed of their ambitions. Today, more than 35 million users and 7,000+ customers trust Grafana Labs to ensure reliability of their applications and systems, resolve incidents quickly, and optimize their telemetry to reduce noise and cost.

We are a 100% remote company with 1,600+ team members across 40+ countries. We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote position. We are considering candidates in Germany, Ireland, Sweden, Spain and the UK only.

The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business via general data analytics. Our goal is to make Grafana the single best place where humans and AI agents understand and act on data from across the enterprise.

What You’ll Be Doing:

• 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.
• 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.
• 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.
• Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows.
• Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
• 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.

What Makes You a Great Fit:

• Strong engineering skills: Solid experience building production-grade, user-facing software systems.
• AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory.
• Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset.
• Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions.
• Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table.

Requirements:

• 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.

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.