### Description

Add a process_line callback to KubernetesPodOperator 
Like https://github.com/apache/airflow/blob/main/airflow/providers/apache/beam/operators/beam.py#LL304C36-L304C57 the `BeamRunPythonPipelineOperator`, which allows the user to add stateful plugins based on the logging from docker job 

### Use case/motivation

I can add a plugin based on the logging and also allow cleanup on_kill based on the job creation log. 

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

self.pod_request_obj = self.build_pod_request_obj(context)
        self.pod = self.get_or_create_pod(  
            pod_request_obj=self.pod_request_obj,
            context=context,
        )
        self.invoke_defer_method()
    def invoke_defer_method(self):
        """Method to easily redefine triggers which are being used in child classes."""
        trigger_start_time = utcnow()
        self.defer(
            trigger=KubernetesPodTrigger(
                pod_name=self.pod.metadata.name,
                pod_namespace=self.pod.metadata.namespace,
                trigger_start_time=trigger_start_time,
                kubernetes_conn_id=self.kubernetes_conn_id,
                cluster_context=self.cluster_context,
                config_file=self.config_file,
                in_cluster=self.in_cluster,
                poll_interval=self.poll_interval,
                get_logs=self.get_logs,
                startup_timeout=self.startup_timeout_seconds,
                base_container_name=self.base_container_name,
                on_finish_action=self.on_finish_action.value,
            ),
            method_name="execute_complete",
        )
    def execute_complete(self, context: Context, event: dict, **kwargs):