After a lot of trial-and-error and a LOT of research, I've discovered the following:
Kettle doesn't support load-based distribution, only round-robin (It's typically used to distribute rows of data to different steps, so load / execution time is almost never a factor)
Round-robin-only distribution means my each Job in the distribution will handle the same number of results (in my case, each Job Executor step handles 9 transformations, regardless of how long each one could take.)
The workaround (round-robin distribution rather than true parallelization) was simpler than I thought, once I fully grasped the manner in which Kettle processed and passed results, and I only needed to move my job execution step from my parent job to the first Transformation, using the Job Executor step.
Because of this distribution method, it would be beneficial to have long-running results picking up next to each other in the results, so they are distributed evenly across the jobs
I did add a reply to my thread on the Pentaho Forums, providing a picture of my solution.
Unfortunately, per #1, it appears as though there's no support for my original goal.