You can try something like below:
skip = np.ones((nIndiv,), dtype=int)
skip[nIndiv-1] = 0
with pm.Model() as model:
...
sigma_indiv = pm.HalfNormal('sigma_individual', sd=sigma_indiv_upp, shape=5)
delta = pm.Normal('delta_individual', 0., 1.)
a_individual = pm.Deterministic('individual_eff', a_group[groups] + delta * sigma_indiv[groups] * skip)# so that the skip one just adding a zero.