The process included an initial conversation with the hiring director, followed by system design and product peer interviews. The role was presented as a Frontend Engineering Manager position. During the interview with the product manager I was told AI expertise was not required for this role. Later there was an additional conversation with an engineer from the AI team. Since the earlier interviews clearly stated AI was not relevant for the role, the discussion stayed high level and focused on general awareness rather than deep technical details. The feedback later listed lack of AI expertise as one of the reasons for rejection. This created confusion because the expectation was explicitly described as not required earlier in the process. Other feedback also introduced requirements that were not mentioned in the job description, such as specific tooling like Sentry and deeper platform incident management responsibilities. Overall the process suggested misalignment between interviewers from different teams and unclear evaluation criteria. The role has been open for a long time, and the changing expectations across interview stages may explain why the position remains difficult to fill.

The first stage of the interview process was great—easy and a genuinely interesting conversation. The second interview with the hiring manager, unfortunately, was a notable contrast. The manager's perspective on management seemed behind the times. The interview felt dry, as if the manager was simply reading questions without engaging in a fluid discussion. Candidates should know that moving forward seems to require preparing very formal answers and following the STAR methodology to the letter.