After the initial recruiter screening, my next step was supposed to be an interview with a Director, but due to scheduling issues, that discussion never happened. Instead, I moved directly to what became the third round, described as a mix of technical and behavioral assessment.
To my surprise, the interviewer was a recently promoted manager with around four years of experience and an undergraduate degree. Naturally, I expected a few in-depth technical questions — especially since the job description emphasized LLM development, fine-tuning, and AI solution delivery. However, the conversation turned out to be more behavioral and leadership-focused.
The interviewer asked several standard management-style questions, including:
- How do you manage your team?
- How do you handle low performers or conflicts within the team?
- Tell me about a project that had the highest business impact.
These questions were quite generic — in fact, I later recognized them as identical to some asked by a senior director during a fifth-round interview at Slalom. It seemed the interviewer may have borrowed them from a shared question bank or prior templates rather than drawing from real technical depth.
When given a chance to ask questions, I inquired about how PwC plans to fine-tune large language models (LLMs) — since this was explicitly mentioned in the job description. Unfortunately, the interviewer admitted he wasn’t very technical and didn’t work closely with that side of AI. That exchange highlighted a mismatch between the expected role’s scope and the interviewer’s background, which sometimes happens in large organizations where multiple layers of management exist.
Ultimately, I received a rejection. But the takeaway was clear — not every interview reflects your capability. Sometimes it’s about who happens to be on the other side of the table.
Key Lessons for Aspiring Candidates
- Expect variability in interviewers’ technical depth.
At firms like PwC, your interviewer might come from a project management or delivery background rather than hands-on engineering — adjust your tone and examples accordingly. - Always be prepared for generic leadership questions.
Even technical roles at the manager level focus heavily on how you manage people, drive outcomes, and influence decisions. - Clarify the role’s technical expectations early.
If the description mentions “AI/LLM training,” be ready to ask detailed questions about whether it’s actual model development or simply AI project oversight. - Don’t take rejections personally.
Sometimes, rejections reflect internal misalignments, timing, or lack of fit between interviewer expectations and your specialization — not your skills or potential.
*Written by the Value Learn Team— based on voluntary contribution from an alumnus