Grafana Labs is looking to solve the problem of making sense of complex observability data through AI-driven features, reducing toil, lowering the barrier of domain expertise, and surfacing meaningful signals from noisy environments.
Requirements
- 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.
Responsibilities
- 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.
- 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.
Other
- This is a remote opportunity and we would be interested in applicants from USA time zones only at this time.
- 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.
- 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.
- 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.
- 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.
