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AI mock interview for AI and LLM Engineers
RAG, evals, agents and cost control — practice explaining how you build reliable products on large language models.
Free 10-minute interview with a full report. Paid plans run full-length sessions.
AI Engineer interview questions you might get
A sample of the starting questions. The live interview follows up on your answer, so no two sessions go the same way.
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Your RAG chatbot answers confidently with wrong facts. How do you debug it?
What it tests: Retrieval versus generation failures.
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How would you build an eval set for a support assistant before launch?
What it tests: Evaluation discipline.
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A user pastes text that tells your agent to ignore its instructions. What do you do?
What it tests: Prompt injection defense.
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How do you cut cost per request by half without losing quality?
What it tests: Routing and caching trade-offs.
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When is fine-tuning worth it compared to better prompts or retrieval?
What it tests: Judgment on approach.
How a session works
About 20–30 minutes from setup to report. End any time and you still get feedback on what was covered.
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Set your target
Pick a role, level and stack. Add a job description or your resume if you want questions about your real projects.
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Answer live
Speak or type. The interviewer follows up on thin answers, raises the difficulty when you're doing well and switches to code when it fits.
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Read the notes
A report scores every competency, quotes the answers that cost you, and gives you a prep plan for the next session.
A report that quotes you, not a pat on the back
Every score links back to something you actually said.
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Competency scores
Weighted to the role you picked, so a system design gap counts more for a senior backend role than for a frontend junior.
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STAR check on every story
See which part of each behavioral answer was missing — usually the Result.
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How you sounded
Filler words, hedging, "I" versus "we", and whether you cited real numbers — measured from your words, and compared between the first and second half of the interview.
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A prep plan
The two or three things to practice next, and a skill graph that tracks them across sessions.
Competencies — sample report
STAR — "Tell me about a missed deadline"
How you sounded
Questions
Is this for ML researchers?
No. It's for engineers building products on top of LLMs. Use the Machine Learning Engineer track for model training roles.
Which providers or frameworks?
Questions are provider-neutral. Add specific tools to your stack if you want them covered.
Does it test coding?
It can ask you to sketch code for a pipeline or tool call, reviewed with your explanation.
Is it free to try?
Yes. Each month you get a free interview of up to 10 minutes with its scored report. Paid plans add full-length interviews, every track and the full 360 report.