The process of finding the optimal network architecture for your problem is the heart of the deep learning process - that's where you use your prior knowledge to optimize performance.
Honestly, I don't really see how a GUI as you suggested could serve this purpose, as:
To be able to assess a given architecture, you need to train the net on your data (from scratch). For deep neural networks this is a process that could take a while. So if every click you make requires an hour's computation, it pretty much takes the entire advantage of a graphic UI off.
Most implementations (caffe, TensorFlow) have such simple syntax, that changing the architecture (changing up layers, tuning the hyper-parameters) really just comes down to changing the value of a single string or constant: nothing you really need a GUI for.
If, on the other hand, what you are looking for is a more systematic approach to the parameter tuning business, you could read up on Automated Parameter Tuning.