I don't think all Ph.D. students or any ordinary engineer can take a vaguely defined research problem and make it succeed. Ph.D. doesn't necessarily prepare you for the research part; it does, however, prepare you to advertise a very /bad solution/ as a novel contribution. It wasn't always like this, but it has come to it. It takes credibility, curiosity, character, and of course, research skills to solve a vaguely defined problem---none of which are given to you by a Ph.D. degree.
I have worked at two FAANGs, and more often than not my interactions with Ph.D. degree holders have left a bad taste in my mouth. Speaking of which, there was one person that was "selling" an event timeline as a root cause analysis system that does "temporal" correlation (with no filtering or association at all) :). And another person that was advertising a DFS compilation of a neural net during the training phase (as opposed to the typical BFS that people do) as a superior and novel contribution that changes how we think about neural nets or something along those lines.
A good engineer would have laughed at both after carefully considering all aspects of the problem.
I suspect that Ph.D. "engineers" are more desirable because of their broader skillset (they have worked with more tools and have taken more classes) and also the fact that companies can hire them at almost the same cost as a BS/MS degree holders. Plus universities have already done some filtering on Ph.Ds.