AI technical interviews for engineering roles

Questions about what the candidate has actually done

AI Hiring reads the resume and writes questions about the technologies and projects on it, for example how they trained an object-detection model, or why they chose a particular database. Add the job description and the questions focus on what the role needs; set the experience level so the questions match a fresher or a senior engineer.

Follow-ups that separate real experience from buzzwords

A good answer about a specific tool gets a deeper follow-up on that tool: a trade-off, an edge case, or why they made a choice. That is how you tell someone who has really used it from someone who only knows the name. A weak answer moves on to another skill instead of drilling into what they don't know.

Every answer graded the same way

Each answer is scored out of 10: key points covered (with quotes from the answer), depth and clarity. Accent, filler words and transcription errors are never penalised, a clearly wrong technical claim loses a mark, and a correct approach that differs from the expected one still earns credit. The skills the job description requires count double in the overall score.

Add a coding round

After the interview, send the candidate a coding assessment. They solve the problems in the browser and you review their code and results alongside the interview report.

Your engineers stay in control

The report is evidence for your team, not a verdict. Your engineers review the scores and quotes and decide who moves to the next round, without spending their time on every first-round call.