An AI interview for software engineers usually mixes a résumé walk-through, a deep dive into a project you built, spoken explanations of technical ideas and behavioral questions, and some add a system design or coding discussion. The AI typically transcribes what you say and rates it against a rubric built from the job description, so you score well by naming your own decisions, stating trade-offs out loud, giving real numbers and keeping each answer structured.
This is a preparation guide. It covers how AI-run interviews read engineering answers and how to practice for them.
What an AI interview for software engineers covers
Formats vary by employer and vendor. As of October 2026, Mercor's candidate guide says most of its interviews take about 20 minutes and that some "are technical and require deep discussion of prior experience." HireVue says its AI Interviewer suggests questions and answer rubrics based on the job description, asks probing follow-up questions and ties scores to behavioral anchors, and that recruiters always make the final call.
| Part | What you're asked (example) | What the rubric likely rewards |
|---|---|---|
| Background | "Walk me through your experience." | A 60 to 90 second summary tied to the job's stack and level |
| Project deep dive | "Tell me about a system you built." | Your decisions, constraints, trade-offs and a measured result |
| Technical concept | "Explain eventual consistency." | A correct definition, a real example and when it breaks down |
| System design | "How would you design a URL shortener?" | Requirements first, then components, a bottleneck and trade-offs |
| Behavioral | "Tell me about a disagreement in code review." | Your actions, how you resolved it and what shipped |
| Coding (some interviews) | A problem to solve and explain | A stated approach, complexity and test cases, within the platform's instructions |
Every row rewards the same habit: say the reasoning, not just the conclusion. A transcript only contains what you said, so a good decision you never explained doesn't exist for the scorer.
Project deep dives: the story that carries the interview
Engineers often under-score here because they describe the system instead of their part in it. Use this order:
- The problem and why it mattered, in one sentence.
- The constraints: scale, deadline, team size or legacy code.
- Your decision, and the option you rejected.
- The result, with a number.
- What you'd change now.
Example: "Our order-history page was timing out for large customers, and support was getting about a dozen tickets a week about it. I owned the fix on a team of four, with two weeks before a big client onboarding. The page ran a five-table join on every load. I considered read replicas, but they would have taken longer to set up than we had, so I proposed a precomputed summary table updated by an event consumer, with the old query kept as a fallback behind a feature flag. I wrote the consumer and the backfill job, and ran both versions side by side for three days to compare results. The p95 load time dropped from around 9 seconds to under 1, and the tickets stopped. If I did it again, I'd add a reconciliation check from day one; we found a drift bug a month later that it would have caught."
That answer names the trade-off, uses "I" for the work, gives a result and ends with a credible lesson, which is exactly what a follow-up would probe next. For more project examples, see "describe a challenging project" answers for engineers.
Explaining technical ideas out loud for a transcript
In a voice interview there's no whiteboard, so your explanation has to work as plain text. Four habits help:
- Define before you use. Spell out an acronym once: "a CDN, a content delivery network."
- Signpost. "There are two parts to this. First… Second…"
- Use a concrete example from a system you've worked on.
- Name the trade-off. A strong technical answer says when the approach is the wrong choice.
Here is the difference for the question "Why would you add a cache?"
| Version | Answer (example) | What a scorer can use |
|---|---|---|
| Before | "Caching makes things faster, like Redis, so you just cache stuff and it's quicker, unless it's stale, which can be an issue." | A tool name and a vague risk. No definition, example or decision. |
| After | "A cache stores the result of an expensive read so repeat requests skip the database. On our product catalog, an in-memory cache brought most reads down to a few milliseconds. The trade-off is staleness: if prices change, users can see old data, so we set a short expiry and cleared the entry on every price update. I wouldn't cache data that must be exact on every read, like account balances." | A definition, a real result, a named trade-off, the mitigation and a boundary case. |
For more on this format, see technical questions in an AI voice interview.
System design and coding questions with an AI interviewer
When a voice interviewer asks a design question, talk through it in a fixed order so the transcript reads like a short design doc:
- Clarify requirements and scale: users, reads versus writes, latency targets.
- Describe the main components and how data flows between them.
- Pick one bottleneck and explain how you'd handle it.
- State the trade-offs you're accepting and what you'd revisit at ten times the load.
If a coding task is part of the interview, follow the platform's instructions exactly. State your approach before you write, give the time and space complexity, and walk through a test case or two out loud, including an edge case. The free system design cheat sheet and coding interview cheat sheet are good refreshers before practice, and our guide to the coding interview with an AI interviewer covers that format in depth.
Behavioral questions for engineers
Engineering rubrics often score collaboration, ownership and communication alongside technical skill. Prepare one story for each of these common prompts, and keep "I" for your own actions:
| Prompt | Competency | Story to prepare |
|---|---|---|
| "Tell me about a production incident." | Ownership under pressure | What broke, what you did in the first hour, the fix, the postmortem change |
| "Tell me about a disagreement in code review." | Collaboration | The technical point, how you settled it with evidence, what shipped |
| "Tell me about a time you missed a deadline." | Planning and candor | When you raised the risk, the trade-off you made, your new habit |
| "Tell me about learning a new technology fast." | Learning | What you learned, how, and what you delivered with it |
| "Tell me about a time you improved a process." | Initiative | The pain point, your change, the measured result |
If a story is good but loosely told, the free STAR story builder lays it out in a few minutes.
Practice with a Mock Interview mix
Take the assessment yourself and follow the employer's rules — use CoPilot Interview to practice beforehand. The practice that transfers best is spoken, timed and scored.
- Set up a realistic mix. Our free AI interview assistant includes a Mock Interview mode that builds the interview from your résumé and the job description. You choose the level, 3, 5 or 8 questions, a mix of behavioral, technical, system design and coding, and your coding language. It reads each question aloud, scores each spoken answer out of 10 with what to fix and a model answer, then gives you a report card. Coding questions never auto-submit, so you can think in silence.
- Re-answer your lowest score in your own words, borrowing the model answer's structure, not its sentences.
- Add variety in the browser. The free demo has 145 real interview questions across 10 tracks, graded by AI.
- Repeat daily for a week. The free plan includes 15 minutes every day, with no card and no signup.
CoPilot Interview is not affiliated with Microsoft Copilot or GitHub Copilot. For drills by round, see our round-by-round software engineering prep guide, and for recorded question sets, HireVue software engineer questions.
Rehearse your project story and design answers
Get each spoken answer scored out of 10 with what to fix and a model answer, across behavioral and technical questions. Free in your browser.
Try a free AI mock interviewFAQ
What questions are asked in an AI interview for software engineers?
Usually a background walk-through, a project deep dive, technical concept questions and behavioral questions, sometimes with a system design or coding discussion. The mix depends on the employer and the level of the role.
Does the AI score my code or my explanation?
It depends on the platform. Many AI interviewers work from a transcript, so your spoken explanation of the approach, complexity and trade-offs is what gets rated. If code is submitted, follow the platform's instructions and explain it as you go.
How technical should my answers be?
Technical enough to be correct and specific, with terms defined once. Name real tools, numbers and trade-offs from your own work, and avoid long strings of jargon that read poorly in a transcript.
Will an AI interviewer ask follow-up questions?
Conversational ones often do. HireVue says its AI Interviewer asks probing follow-up questions, so prepare a second layer of detail for every project you mention: why you chose it, what went wrong and what you'd change.
Is a human involved in the hiring decision?
Usually. Many tools produce scores, transcripts or summaries that recruiters review. HireVue says recruiters always make the final call on its AI Interviewer; other vendors and employers set their own process.
Can I use an AI coding tool during an AI interview?
No. Do the interview on your own and follow the employer's rules. Use scored mock interviews and the free cheat sheets to prepare beforehand.