Scaling Personalized Interview Practice with AI
To strengthen candidate experience and improve hiring quality.
ROLE
Lead Designer & Developer
TIMELINE
2 weeks
IMPACT
Post-Amazon proof of concept
Business Goal
At Amazon, roughly 30K employees go through interviewer training every year. I was part of leading the revamp of that program. The goal was to improve interviewer proficiency at scale. Better interviewers create better candidate experiences, which directly affects hiring quality and employer reputation.
Problem Statement
Even after revamping the program, one problem remained. Training happened weeks or months before an interviewer ever sat down with a candidate. By the time the interview came, skills hadn't been practiced recently. We had scale. What we didn't have was training close enough to the actual interview to make a difference.
Solution
After leaving Amazon, I built the solution I wished we'd had. An AI-driven simulation that identifies when an interviewer last practiced, detects upcoming interviews on their calendar, and delivers a tailored, realistic practice scenario just before they need it, with actionable feedback built into the experience itself.