Staff AI Engineer - Grafana AI/ML | USA | Remote

Grafana Labs

1d•$174,986 - $220,000•Remote

About The Position

Grafana Labs is seeking a Staff AI Engineer with a strong software engineering background, a quick iteration mindset, and a passion for experimentation to join their AI teams. This role focuses on developing AI-driven features to help users make sense of complex observability data, reduce toil, and surface meaningful signals. The AI teams operate with a high degree of autonomy and ownership, empowering engineers to make decisions and move quickly. The Staff AI Engineer will work closely with cross-functional teams to develop, test, and ship AI-powered features that improve infrastructure and observability quality through automation, and expand the capabilities of AI agents across the observability stack for incident response. The role offers broad opportunities for expansion based on impact and initiative. Grafana Labs encourages pragmatic AI-assisted development, providing access to modern AI coding assistants and frontier models.

Requirements

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.
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.
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.
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.
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.

Nice To Haves

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.

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.
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.