tf.Variable is the equivalent of nn.Parameter in PyTorch. tf.Variable is mainly used to store model parameters since their values are constantly updated during training.
To use a tensor as a new model parameter, you need to convert it to tf.Variable. You can check here how to create variables from tensors.
If you want to add a model parameter in TensorFlow inside the model itself, you could simply create a variable inside the model class and it will be automatically registered as a model parameter by TensorFlow.
If you want to add a tf.Variable externally to a model as a model parameter, you could manually add it to the trainable_weights attribute of tf.keras.layers.Layer by extending it like this -
model.layers[-1].trainable_weights.extend([new_parameter])