Finding the deterministic autocorrelation function (ACF) from its power spectrum
The power spectral density is the fourier transformed ACF. So what you have to to is to do the inverse fourier transform of the spectrum. And since the spectrum is a rectangle in frequency, it will be a $\frac{\sin(x)}{x}$ in the time domain.

Additionally:


  I know that the power spectrum is the DTFT of the ACF at 0


The signals power is given by $\phi_{xx}(\tau = 0)$:
$$
\phi_{example}(\tau) = \int_{-\infty}^{\infty} x_{1}(t)* x_{2}(t-\tau)\mathrm{d}x
$$
If you autocorrelate (correlate a signal with itself), your subscripts vanish ($ x_1, x_2$ become $x$) and if you calculate the ACF at $\tau = 0$ you will get the squared power of the signal:
$$
\phi_{example}(\tau = 0) = \int_{-\infty}^{\infty} x(t)* x(t)\mathrm{d}x = \int_{-\infty}^{\infty} x(t)^2\mathrm{d}x
$$

If your signal does not have a finite amount of energy, you will have to use the following definition of the ACF:
$$
\phi_{example}(\tau) = \lim_{T \to \infty} \frac{1}{T}\int_{-\frac{T}{2}}^{\frac{T}{2}} x(t)* x(t-\tau)\mathrm{d}x
$$