Senior Fullstack Engineer - Grafana Analytics

At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business via general data analytics. Our goal is to make Grafana the single best place where humans and AI agents understand and act on data from across the enterprise. We build systems that help users make sense of their sea of data through AI-driven features in use cases like product analytics and sales data. These capabilities lower the barrier of domain expertise and surface meaningful signals from messy data.

The Grafana Analytics team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership.

We’re looking for a Full-Stack Software Engineer with a strong software engineering background, a quick iteration mindset, and a passion for experimentation – balanced by a focus on shipping and scaling impactful features that deliver value to users. This new team works like a startup within the company: you'll wear multiple hats and won't rely on cross-functional teams that typically support other teams inside Grafana Labs engineering. You will design, develop, test, and ship AI-powered features that can manage dealing with large datasets, while also expanding the capabilities of analytics-focused AI agents to assist users with information retrieval. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative.

Key responsibilities:

• Build and deliver full-stack user experiences: 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 rest of the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems while engaging with internal data teams for dogfooding.
• 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.

What we're looking for:

• Product mindset: You understand what problems users have and develop solutions to address those with proficiency and taste.
• Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions 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 your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table.

Requirements:

• Track record of building user-facing experiences that strike the right balance between utility and delighting the user.
• Experience with LLMs, context 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 have (but not required):

• Experience building or working with agent frameworks or multi‑agent workflows.
• Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks)
• Experience building tools for data engineering.

Compensation & Rewards:

In the USA the Base compensation range for this role is $154,445 - $185,334. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally.

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