As the other answer states, $x = (x_1,x_2,x_3,x_4)$ will be a generalized eigenvector but not an eigenvector if and only if $x_4 \neq 0$.
However, when applying the usual procedure recommended for finding the Jordan form, it is convenient to be able to find a generalized eigenvector by solving the equation $(A - I)x = v$ for a suitable eigenvector $v$ so that the vectors $x,v$ can be used in a chain.
With that in mind, suppose that we don't know the generalized eigenvectors of this matrix. we are looking for an eigenvector $v$ such that the equation
$$
(A - I)x = v
$$
has a solution. Note that we have
$$
A - I = \pmatrix{0& 0& 0& -3\\ 0& 0& 0& 3\\ 0&0& 0& -1\\0& 0& 0& 0}.
$$
In order for $(A - I)x = v$ to have a solution, $v$ must be an element of the column-space of $A - I$. So, $v$ must be a (non-zero) multiple of $(-3,3,1,0)$. We can simply take $v = (-3,3,1,0)$ (and note that $v$ is indeed an eigenvector of $A-I$). We now solve the equation $(A - I)x = v$ in the usual fashion:
$$
\left(
\begin{array}{cccc|c}
0& 0& 0& -3&-3\\ 0& 0& 0& 3&3\\ 0&0& 0& -1&-1\\0& 0& 0& 0&0
\end{array}
\right) \leadsto
\left(
\begin{array}{cccc|c}
0& 0& 0& 1&1\\ 0& 0& 0& 0&0\\ 0&0& 0& 0&0\\0& 0& 0& 0&0
\end{array}
\right).
$$
In other words, our system of equations is equivalent to $x_4 = 1$, so any vector $x$ with $x_4 = 1$ solves the equation $(A - I)x = v$.
With that having be done, we can extend $x,v$ to get the following Jordan basis of $A$:
$$
\{v,x,e_1,e_2\} = \{(-3,3,-1,0),(0,0,0,1),(1,0,0,0),(0,1,0,0)\}.
$$
As Klaus's answer notes, there are other strategies for handling eigenspaces of dimension greater than $1$.