At Grafana, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. The Grafana AI teams play a key role in this mission by helping users make sense of complex observability data through AI-driven features. These capabilities reduce toil, lower the barrier of domain expertise, and surface meaningful signals from noisy environments
What makes our team different is how we work: we operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership
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. You’ll work closely with cross-functional teams to develop, test, and ship AI-powered features that contribute to improving infrastructure and observability quality through automation, while also expanding the capabilities of AI agents across the observability stack to assist users with incident response. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative
Curious about what it's like to build AI at Grafana?
Build and deliver AI solutions: Take ownership of developing high-performance AI features to help users detect, triage, and resolve incidents using observability data and tools
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 incident lifecycle management and automated analysis tasks
Collaborate cross-functionally: Work with data analysts, product managers, and designers to shape AI-driven product features, including integration of agentic components with internal tools, alerting systems, runbooks, and developer workflows
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
We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always with strong code review and quality standards. You'll also have access to the latest frontier models from OpenAI, Anthropic, and Google