As a founder, you're faced with many challenges, and one of the major ones is hiring, especially for new roles that don't yet exist in the company. I've had to hire our first engineer, data analyst, data scientist, and many more. Obviously, I'm not an expert in all these domains, but I was able to hire experts by consistently applying the same approach.
Our hiring process involves a personal interview, professional interview, reference call, concluding interview, and an offer. Most steps are similar across different roles, so I'll focus on the professional interview. The first step is understanding the role. I assume one of the founders is actively doing this work. If not, it might be challenging to apply my approach. List down the challenges and responsibilities for the role, order them by importance, and think about the day-to-day impact of this role on the company. So far, nothing new. You probably know it already.
The tricky part is the professional interview. Many companies follow an approach I have little belief in, conducting interviews unrelated to the role. We're all familiar with companies asking web developers to sort an array and other irrelevant computer science questions. My approach is to convert the role's challenges into the interview questions. For example, when hiring a web engineer, the interview involves live coding to develop an actual feature on our codebase. A backend engineer is asked to design a system we already have, like our feed or content pipeline. A data scientist builds a recommendation model using a dataset we provide. We never use their work beyond the interview. Key aspects include limiting the interview time to respect the candidate's time and paying for their efforts, as these are usually lengthy interviews. We set clear expectations: we don't expect a complete solution or production-grade, but we are keen to see how they think and approach these challenges.
To successfully convert challenges into interview tasks, it's crucial to focus on the core of each challenge while minimizing dependencies. For instance, if assessing frontend skills, consider using a mock function to fetch data or setting up a mock server beforehand to simplify the process. Also, be mindful of the time required for candidates to understand the context at the beginning of the interview. Typically, the amount that can be realistically accomplished is less than anticipated, so it's wise to adjust your expectations accordingly. I often start with warm-up questions related to the task or domain to ease into the interview and gauge their knowledge. For example, I might ask a backend engineer about their experience with change data capture or a data scientist about various methods for building recommendation systems.
Like everything, it takes practice. My first interviews weren't great, but slowly, we improved as a company and fine-tuned the process to match our needs precisely. Our hiring process is all about mutual fit and respect. We want the candidates to be sure we're the right place for them, as much as we want to be sure they fit our team. Our professional interview gives them a taste of the challenges they'll face and allows us to pair with them on the task to see how they handle it.
Candidates often express appreciation for this approach. We've received positive feedback on numerous occasions about our hiring process, particularly the professional interview. Initially, some candidates are skeptical when we introduce this idea, but by the end, they usually see the value of our unique approach for themselves. With that said, sometimes we have to adjust. In the data scientist interview, we received several comments about the stress induced by live coding. In response, we changed the format to better align with the feedback. I strongly encourage seeking feedback, which can significantly refine and shape your hiring process.
Hiring for a new role is challenging and full of unknowns. Unravel this mystery by turning the challenges you face in doing this job into an interview. Focus on expectations alignment, mutual fit, respect, and feedback. We scaled from 3 founders to over 20 members with various roles (developers, product managers, marketing, devrel, analysts, data scientists, HR, and more). It works!