Manager; AI Evaluation Engineering
Posted Sep 21, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
Tell me about a time you built or led a team where you had to identify skill gaps and close them.
What they are checking: Whether they actively develop people, which the posting stresses as part of owning team performance.
Tell me about a time your evaluation results turned out to be misleading. How did you find out?
What they are checking: Humility about measurement and the habit of checking whether metrics actually track what users experience.
What would you do
A product team wants to ship a generative AI feature next week, and your evaluation shows a hallucination rate you're not comfortable with. What do you do?
What they are checking: Whether they can hold a quality bar under pressure while offering a realistic path forward instead of a flat no.
How would you explain evaluation results to an executive who just wants to know if the product is ready?
What they are checking: Ability to translate statistical results into a clear decision and its risks for a non-technical audience.
How do you balance your team's time between building evaluation tooling and running evaluations for many product teams?
What they are checking: Whether they invest in reusable infrastructure rather than staying stuck doing one-off manual reviews.
About the work
How would you design an evaluation for a digital assistant that answers dealer questions about equipment and parts?
What they are checking: Whether they can turn a fuzzy goal like helpfulness into measurable criteria, test sets and pass thresholds.
What is your view on using an LLM as a judge, and when would you not trust it?
What they are checking: Whether they understand the bias and drift of automated graders and know when human review is required.
How do you evaluate an intelligent agent that takes multiple steps and calls tools, compared to a single chatbot answer?
What they are checking: Understanding that agents fail in the path, not only the final answer, so evaluation must cover the steps too.
How do you build and maintain a test dataset that stays representative as real usage changes?
What they are checking: Awareness that stale evaluation sets give false confidence once customers start using the product differently.
How do you test for safety issues like prompt injection, data leakage or harmful advice in a customer-facing assistant?
What they are checking: Whether they treat adversarial testing as core work, not an afterthought, for products that reach customers and dealers.
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Practice this out loudThe full job description
As published by Caterpillar.