Staff AI Engineer (Grafana AI/ML)

Join Grafana, a leading open-source observability platform, as a Staff AI Engineer. In this role, you will develop and deliver AI-powered features that enhance infrastructure and observability quality through automation. You will collaborate with cross-functional teams, utilize AI tools effectively, and take full ownership of the AI solutions you develop. Enjoy a range of benefits, including 30 days of paid vacation, healthcare coverage, retirement planning, professional development opportunities, and a fully remote work environment.

• Prendre en charge le développement de fonctionnalités d'IA de haute performance pour aider les utilisateurs à détecter, à trier et à résoudre les incidents.
• Mettre en œuvre un processus hautement itératif où vous prototypez, testez et validez rapidement avec de vrais utilisateurs.
• Collaborer avec des équipes interfonctionnelles pour façonner les fonctionnalités de produit pilotées par l'IA.
• 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
• Strong engineering skills: Solid experience building production software systems (backend and / or full stack). You’re a self-starter, capable of tackling complex engineering problems with minimal supervision
• Collaborative attitude: You communicate effectively with peers, product managers, and designers. You’re open to feedback, and you bring a solutions-oriented mindset to the table
• 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
• Experience with LLMs, prompt 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
• Experience building or working with agent frameworks or multi‑agent workflows
• Experience with infrastructure / devops related tooling: Kubernetes, Docker, Terraform or similar for deployments
• Familiarity with model fine-tuning techniques
• Experience building observability tooling