Generate dictionary of points on n-sphere
Style
Following PEP8, the official Python style guide, you should use snake_case for your variables and functions names. You should also put a space after comas.
I would also rename the function sphere_points as the &quot;get&quot; is implied by the fact that you call a function (to get a result).
You also happen to not use the dim parameter and, looking at your description, the last one is just len(pList). Unless this length is common to a lot of calls and there is a real benefit to cache it, you can drop 2 out of 3 parameters.
numpy
numpy has vectorized functions  for your main operations: numpy.fabs (or numpy.absolute if you're dealing with complex numbers) and numpy.linalg.norm. Using these might speed things up. Unfortunately, going back into pure Python realm (dict + zip) can't be speed up that way.
However, as pointed out by @200_success in a comment, these answers suggest using np.sqrt(pt.dot(pt)) or np.sqrt(np.einsum('i,i', pt, pt)) for faster results than np.linalg.norm. As always, profile and choose what's best for your use case.
Cache function access
In Python, local symbols are faster to resolve. Which means np.linalg.norm is kinda slow, but norm is faster. And granted you performed norm = np.linalg.norm somehow before, it will produce the same result.
But caching a complex lookup within the same call you use it does not add much, since the complex lookup still need to be performed.
One way to efficiently do it is to use default values for arguments as the lookup will be performed only once and the speedup will occur at each call.
Proposed improvements
import numpy as np


def sphere_points(keys, random_gen=np.random.standard_normal, absolute=np.fabs, norm=np.linalg.norm):
    pt = absolute(random_gen(len(keys)))
    pt = pt/norm(pt)

    return dict(zip(keys, pt))