That’s the expected way of working.
You build your model using regular TensorFlow and when you need to deploy it on a mobile device you use the conversion tool to do that. Just a minor tip, it’s better to save as a a saved_model format and not necessarily in h5 (Save and load Keras models  |  TensorFlow Core 9)
The only blocker you might have is that not all operations are available on TFLite as it’s meant for inference only and it’s focused on speed. But when converting the model, if there’s any issue the tool will tell you.