Can’t you just add a prior to A and B that has the noise distribution you want?
A_noisy = pm.Normal("A_noisy", A, 1)
Where the prior can be any distribution centered around your value A
This has the advantage that your sample can take into consideration gradient information. Otherwise you are in untested territory in PyMC3.