Grafana Labs

Staff AI Engineer to own the AI agent infrastructure and automation platform powering GTM teams. Build multi-agent architectures, LLM integrations, and backend services connecting AI models to internal and third-party data platforms. Ship production systems, define technical direction, and partner with various teams to build scalable, self-service automation. Responsibilities include end-to-end development of multi-agent AI systems, building modular agentic systems, developing reusable agentic skills, implementing observability and feedback loops, establishing governance, building MCP servers and APIs, architecting RAG data flows, and building serverless/containerized services. Also involves partnering with RevOps and Finance, designing workflows, and building self-service systems. Requires 8+ years of software engineering experience, 2+ years applying LLMs/AI to production, proficiency in Python/JavaScript, experience with LLM frameworks (prompt engineering, RAG, function calling), building multi-agent systems, GCP, BigQuery, and understanding LLM failure modes.

Senior Developer Advocacy Engineer to build an open source, in-product learning experience within Grafana, focusing on AI-assisted development and enabling non-engineers to contribute content. The role involves shipping product code for both Grafana Cloud and OSS, with a significant portion dedicated to the Interactive Learning Plugin and its content.

Senior Developer Advocacy Engineer role focused on building an open-source, in-product interactive learning plugin within Grafana. The role involves shipping real product code, enabling non-engineers to contribute content, and utilizing AI-assisted development workflows. Requires strong software engineering fundamentals, AI harness experience (agentic development), or Grafana context.

Senior AI Engineer focused on building and shipping AI-powered features for observability tools, including LLM- or agent-powered workflows for incident management and automated analysis. The role emphasizes rapid experimentation, cross-functional collaboration, and delivering production-ready AI solutions.

Senior AI Engineer focused on building and scaling AI-powered features for observability tools, including LLM and agent-based workflows for incident response and analysis. The role emphasizes rapid experimentation, cross-functional collaboration, and delivering production-ready AI solutions.