THat having said, I would never judge the answer to this question without the context of other questions and answers.
I’ve deep dived, investigated, and fixed tonnes of hard problems.
But my memory doesn’t have an index on them. I can’t think of any on the spot and sort them hardest to easiest.
I can think of achievements (and they end up on the resume of course) but those aren’t necessarily debugging a hardest bug, which is a point in time versus months/years of invested effort.
I used to talk about the difficulties of tracking an IO corruption bug in an adapter card and a hardware vendor that wouldn't assist/acknowledge the bug until a another of their much larger customers started reporting similar problems.
But these days, I like to talk about JIT bugs, because I believe anyone using a JIT in production needs to have their head checked. The last one I found literally took me two weeks of writing a bunch of automated tools and burning a crapton of CPU time hunting for a code sequence corrupting a callee saved register in a chunk of code that had a very high reproduce rate but misbehaved after churning away for a few minutes. AKA by the time the problem occurred it was tens of millions of instructions past the actual corruption. I wasn't even sure it was a JIT bug until I found it. Worse it was in a REALLY common piece of code pretty much everyone with a computer has installed, and had been sitting around for a few years before I happened to bump into a pretty consistent reproducer.
Thankfully JIT bugs are rare in most common language runtimes, but what really kicks the JIT problems up a notch is frequently the difficulty of reproducing them and the near inability to do any kind of static analysis outside of execution tracing to find the bugs.
So like every Java, C#, JavaScript developer?
> hunting for a code sequence corrupting a callee saved register in a chunk of code that had a very high reproduce rate but misbehaved after churning away for a few minutes
If you're able to, I usually build projects with a sanitizer to catch strange bugs like these, but the downside is that most runtimes care very little for standards outside of "this seems to work and it's fast enough" so you get a lot of false positives…