Interesting. The interaction is new and may help explain what's going on. On the univariate level, your model predicts as follows: Your full model includes an interaction between X1 and X2 and therefore the impact of X1 depends on the value of X2. At the point where all other variables are equal to 0, your prediction is as follows (X2 is the left axis and X1 is the right axis, sorry for the small axis titles): Here you can visualize that in certain parts of the predictor space (X2 negative), X1 has the inverse relationship with Y, while in others (X2 positive), X1 has a direct relationship with Y. I hope this helps. To PGStats' point above, if you group your data (100 points in each group, or 1000...depending on how many observations), sorted by X1 (and X2), calculate the average response (between 0 and 1), and plot them, it may help visualize the relationship.
... View more