[jandrewrogers]

It could be worse. My personal recruiting peeve is what I call the "Dunning-Kruger interview", where they ask algorithm questions they don't understand and don't even realize that fact. It is unfortunately common, and made doubly worse when it is plainly my area of expertise and the reason I was recruited in the first place.

More than once, I've been recruited by executives at Famous Tech Company to run major new initiatives involving vast volumes of spatially organized data, since my expertise in that area is well known, but there is a technical diligence step where I am grilled on spatial algorithms by a shockingly ignorant (e.g. doesn't understand R-trees) Principal Engineer or similar who actually believes no one can know more about the space than they do. (If that was the case, they wouldn't be trying to recruit me.) If an interviewer wants to test my expertise, they better be able to have a substantive discussion on the subject matter and understand the limits of their own expertise.

I view algorithm gotcha games as disrespectful of an experienced software engineer's expertise generally. I like to turn it into a substantial discussion about the algorithm class generally; if the interviewer is incapable of having a substantial unscripted discussion about said algorithms, it is a red flag and they have no business asking those kinds of questions. These days, I just walk away from an opportunity when this kind of nonsense happens.

[greglindahl]

... maybe the point of putting you in with the shockingly ignorant Principal Engineer was to figure out if you could work with them?

[jandrewrogers]

Heh, possibly, but in practice it usually appears to stem from complete disinterest -- it is an assignment and they do minimal background investigation. I go along with it, but in one extreme case I had a PE-type flatly accuse me of not understanding the theoretical details of a particular algorithm, being unaware that I invented it (and I never mentioned that). When it gets to that point, it is a lost cause.

Some computer science domains are worse than others. Spatial is particularly bad because very few computer scientists realize the theoretical foundations of spatial data structures are completely different than the more ordinary ones they are familiar with -- their intuitions don't apply.