Staff AI Engineer, Grafana Labs

• 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
• We’re looking for an AI Software Engineer with a strong software engineering background, a quick iteration mindset, and a passion for experimentation – balanced by a focus on shipping and scaling impactful features that deliver value to users
• Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision
• 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. You can deal with ambiguity and are able to define scope where things are loosely defined
• Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table
• 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

Desirable

• As part of our skunkworks initiative, you'll wear multiple hats and won't rely on cross-functional teams that typically support other teams inside Grafana Labs engineering
• You will design, develop, test, and ship AI-powered features that can manage dealing with large datasets, while also expanding the capabilities of analytics-focused AI agents to assist users with information retrieval
• As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative
• 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