What to expect from the Grafana Labs hiring process

To be wildly successful, we need exceptional talent. To attract, interview, and select that talent, our teams align on a set of core hiring principles that define who we hire and how we hire at Grafana Labs. As we scale quickly and globally, we maintain a high bar and a consistent process to hire high-impact people who will add to our culture.

Who we hire

We hire bar-raisers

We would rather leave a role open longer than hire someone who doesn’t make us better. Top talent attracts top talent. A high bar helps us attract and retain exceptional people.  

We hire great teammates

We don’t hire jerks. Technical skill doesn’t outweigh behavior. We want people who will collaborate, respectfully challenge, welcome feedback, unlearn when needed, and iterate for the greater good.

We hire culture adds

We recruit from diverse demographic, experiential, and cognitive backgrounds. We see diversity as a culture "add" that helps us improve our teams, innovate, and deliver better experiences.

How we interview

We treat all candidates like our customers

Every candidate experience reflects our brand. Top candidates are interviewing us, too. Our employer brand is built one candidate interaction at a time. Every candidate deserves a great experience, respect, and a realistic job preview—whether or not we hire them.

Hiring managers are accountable leaders

Hiring managers actively recruit and stay engaged throughout the process. They drive alignment on hiring criteria, acceptable trade-offs, role expectations, and feedback.

We build thoughtful interview teams

We work together to assemble great interview teams based on skill relevance and behavioral assessment ability. The interview team composition impacts both who we hire and the candidate experience we create.  It reflects the teams we aim to build across functions, backgrounds, and perspectives.

We evaluate based on evidence

Resumes are signals, not proof. We use structured, behavioral, and situational interviews to assess:

  • What candidates can do: Technical/functional skills, knowledge, and achievements. 

  • How candidates do it: Values, behaviors, and motivators that can predict success at Grafana Labs.

We use structured criteria

We enter interviews with a clear plan and defined criteria. This ensures a deep and broad assessment, avoids redundant questions, and provides a great candidate experience. Gut feelings and irrelevant questions have no place in our process.

Every candidate goes through the same rigorous process

We make no exceptions for referrals or internal candidates. All candidates are screened and interviewed. We want candidates to describe our interviews as challenging, fair, and deep, and our interviewers as diverse, welcoming, authentic, and prepared.

We use AI responsibly

We use AI to improve job descriptions, interview prep, and process efficiency. However, we will never use AI to make hiring or selection decisions. Final decisions are made by people, using human judgment and context.

How we make hiring decisions

We take smart bets

No candidate is perfect. Every hire involves risk. When faced with a trade-off, we invest in people who need help developing specific technical skills or gaining experience that can be obtained on the job. We don't take risks on candidates who can't demonstrate our guiding principles.

We hire for the long term

We hire for adaptability and growth. Hiring managers think beyond immediate needs and evaluate candidates for future impact across Grafana Labs. We evaluate candidates for today's roles, future roles 1-2 years from now, and other potential roles within the broader organization.

We make timely decisions

We use live debrief discussions, especially when feedback is mixed, to ensure transparent hiring decisions are made by the hiring manager. We aim to decide within two business days of a final interview, knowing top candidates expect speed.

We speak up about bias

Fair hiring is everyone’s responsibility. We assume positive intent and embrace giving and receiving real-time feedback to actively address unconscious bias. If something feels off, we say something.