In general Evolutionary Algorithms are completely different than Neural Networks.
The main aspects that make NNs a good application for GPU programming is that:
1. They are using simple maths (addition, subtraction and multiplication), and
2. They are relying on matrix operations (something that GPUs excel at).
EAs though despite that they are parallelisable (each individual can be evaluated and mutated in parallel) they have an aspect that has difficulties
when you want to run them on GPU. This is the fact that an individual is not a always a simple mathematical equation which can be mapped to GPU operations.
Also you might need to consider that there will be a need to translate the representation of what an individual is to a structure that you can apply GPU computations.
On the aspect of what language to use yes C++ is the go to option. I would suggest to look into Python based approaches also, I know there is PyCUDA and Numba (NumPy on GPU). Also from a fast search I found out that there is Vulkan for Python!
The most important part of this project for me is to model your EA's individuals and evolutionary operators in a manner that can be run on a GPU.
I would maybe 1st develop your project to be running on you machine as test.
Then maybe look for the computing cloud platform, like Azure, Amazon, Google to run your AI project on a larger scale.
Usually the cloud computing platform give a free trial for a month or so if i remember well.