  We present a probabilistic construction of $\mathbb{R}^d$-valued non-linear
affine processes with jumps. Given a set $\Theta$ of affine parameters, we
define a family of sublinear expectations on the Skorokhod space under which
the canonical process $X$ is a (sublinear) Markov process with a non-linear
generator. This yields a tractable model for Knightian uncertainty for which
the sublinear expectation of a Markovian functional can be calculated via a
partial integro-differential equation.
