  We consider a stochastic online problem where $n$ applicants arrive over
time, one per time step. Upon arrival of each applicant their cost per time
step is revealed, and we have to fix the duration of employment, starting
immediately. This decision is irrevocable, i.e., we can neither extend a
contract nor dismiss a candidate once hired. In every time step, at least one
candidate needs to be under contract, and our goal is to minimize the total
hiring cost, which is the sum of the applicants' costs multiplied with their
respective employment durations. We provide a competitive online algorithm for
the case that the applicants' costs are drawn independently from a known
distribution. Specifically, the algorithm achieves a competitive ratio of 2.965
for the case of uniform distributions. For this case, we give an analytical
lower bound of 2 and a computational lower bound of 2.148. We then adapt our
algorithm to stay competitive even in settings with one or more of the
following restrictions: (i) at most two applicants can be hired concurrently;
(ii) the distribution of the applicants' costs is unknown; (iii) the total
number $n$ of time steps is unknown. On the other hand, we show that concurrent
employment is a necessary feature of competitive algorithms by proving that no
algorithm has a competitive ratio better than $\Omega(\sqrt{n} / \log n)$ if
concurrent employment is forbidden.
