What the AI screen is for
For engineering roles, an AI screening interview usually sits before the technical rounds. It rarely asks you to write code. It checks whether you can explain your work clearly, whether your experience matches the role and how you work with other people. Coding tests and system design come later, usually with humans.
This is part 2 of our series on AI interview questions. Part 1 covered the general questions every screen asks. Here are the ones engineers hear most, with spoken sample answers. Speak them; don't read them.
Walk me through a project you're proud of
This is the most common engineering screen question. Pick a project where you made real decisions. Say what it was for, what you built, one hard part and what happened. Keep jargon to what the job posting uses.
At my last job I rebuilt the export feature in our web app. Customers could download their data as CSV, but large accounts timed out. I moved the export into a background job, streamed the file to storage, and emailed a link when it was ready. The hard part was keeping old exports working while we switched over, so I ran both paths behind a flag for two weeks. Timeouts on exports stopped, and support tickets about it went away.
Tell me about a bug that was hard to find
This checks how you reason under uncertainty. The interviewer wants your process: how you narrowed it down, what you tried, what fixed it, and what you changed so it would not recur.
Our mobile app crashed for a handful of users on login, and we couldn't reproduce it. I grouped the crash reports by device and found they were all on one older OS version with a particular language setting. That pointed to date parsing. The server sent a date in a format the old system library read differently. I switched to a fixed format on both ends, added a test with that locale, and the crash stopped showing up in the next release.
Tell me about a trade-off you made
Engineers make trade-offs all day: speed against quality, building against buying, a quick fix against a proper one. Show that you considered both sides and could explain the choice to someone who isn't technical.
We had a launch date and a search feature that was slow on big accounts. A proper fix meant changing the database schema, which would take weeks. I proposed a short-term cache for the most common searches so we could launch on time, and wrote up the schema change as the next task with the risk if we didn't do it. My lead agreed, we launched, and we shipped the real fix the following month.
Tell me about a disagreement in code review
This checks how you handle feedback and friction. Pick a real technical disagreement, show you listened, and show how it got settled, ideally with evidence rather than seniority.
A senior colleague asked me to rewrite a function I'd split into small helpers; he found it harder to follow. I thought the split made testing easier. Instead of going back and forth in comments, I asked for fifteen minutes on a call. We agreed to keep two helpers that had their own tests and fold the rest back in. I learned to ask what a reviewer is worried about before defending my version.
Other questions to prepare
- Why do you want to work on this product or team?
- How do you keep your skills current?
- Describe a time you had to learn a new language, framework or tool quickly.
- How do you decide when code is ready to ship?
- Tell me about a time a deadline slipped and what you did.
- What would you want to learn in your first three months here?
Many AI screens also ask about specific lines on your résumé, so be ready to explain any technology you list. If you put it on the page, expect a question about it. For a broader role-specific list, see our software developer practice page.
How to practice for it
Engineers often prepare hard for coding rounds and not at all for the talking rounds. Spend two or three short sessions saying these answers out loud. Time yourself; two minutes is plenty. Listen for jargon a recruiter would not follow and for answers where 'we' hides what you did. The STAR method helps structure the stories.
For practice that asks about the projects on your own résumé and follows up when an answer is vague, you can rehearse with Hmmlo. Its AI interviewers ask spoken questions, and a coach review afterwards shows which answer to fix.
