Staff AI Engineer (Grafana AI/ML)
Grafana Labs
full-remoteleadpermanentbackendfullstack Full remote 26 days ago via WTTJ
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LLMsPrompt EngineeringGenAIAgentic WorkflowsAWSGCPKubernetesTerraformObservabilityFine-tuning
About the role
Role overview
Join Grafana Labs as a Staff AI Engineer (Grafana AI/ML). You will design, build, and deliver AI-powered features that enhance infrastructure and observability, with ownership of the AI solutions you develop.
Key missions
- Develop high-performance AI features to help users detect, triage, and resolve incidents.
- Build a highly iterative process: prototype, test, and validate quickly with real users.
- Collaborate with cross-functional teams to shape AI-driven product features.
Responsibilities
- Ship AI prototypes and iterate based on feedback.
- Drive projects forward with strong ownership and comfort with ambiguity.
- Partner with product managers and designers; communicate clearly and incorporate feedback.
- Deliver AI applications and systems that reach production and are actively used.
Requirements
- Strong engineering skills with experience building production software systems (backend and/or full stack).
- Proven initiative and ability to define scope when requirements are loosely defined.
- Practical AI experience focused on real-world delivery.
- Experience with LLMs, prompt engineering, and GenAI applications.
- Track record of delivering production software used by customers/users.
- Exposure to cloud-native environments (AWS, GCP, or Azure).
- Experience using observability tools to understand and troubleshoot system behavior.
- Experience with agent frameworks or multi-agent workflows.
- Infrastructure/DevOps tooling experience: Kubernetes, Docker, Terraform (or similar).
- Experience building or working with observability tooling.
- Familiarity with model fine-tuning techniques.
Nice-to-haves / differentiators
- Comfortable releasing prototypes early and iterating rapidly with pragmatic experimentation.
About Grafana Labs
Grafana Labs is a company focused on observability and monitoring tools used to understand and troubleshoot infrastructure and application systems. The role centers on building AI-powered capabilities (Grafana AI/ML) to improve incident detection, triage, and overall observability quality.
Scraped 6/29/2026