The Opportunity
At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems. We are launching a skunkworks initiative to bring observability to the broader business via general data analytics, making Grafana the central hub for humans and AI agents to act on enterprise data. We are looking for an engineer to help us build systems that surface meaningful signals from complex data sets.
What You’ll Be Doing
- Build and deliver AI solutions: Take ownership of developing delightful, high-performance AI features to help users discover, organize, and optimize access to large datasets.
- 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 the data engineering lifecycle.
- Collaborate: Work with the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems.
- Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows.
- Effective communication: Contribute across teams in a highly dynamic and collaborative environment.
- Ownership and impact: Ensure solutions are scalable, maintainable, and aligned with real user workflows.
What Makes You a Great Fit
- Strong engineering skills: Solid experience building production-grade, user-facing software systems with the ability to make UI design decisions.
- AI experience with a practical mindset: Familiarity with AI technologies and frameworks, focusing on delivering high-quality, real-world solutions.
- Quick iteration and experimentation: Comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset.
- Proven initiative: Ability to take ownership, drive projects forward, and define scope in ambiguous environments.
- Collaborative attitude: A solutions-oriented mindset with openness to feedback.
Requirements
- Experience with LLMs, context engineering, and building applications powered by GenAI.
- Proven track record of delivering production-ready software.
- Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure).
- Experience using observability tools to understand and troubleshoot system behavior.
Bonus Points
- Experience building or working with agent frameworks or multi‑agent workflows.
- Experience as a data analyst or working with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks).
- Experience building tools for data engineering.