### 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)

pod = k8s.V1Pod(
            api_version="v1",
            kind="Pod",
            metadata=k8s.V1ObjectMeta(
                namespace=self.namespace,
                labels=self.labels,
                name=self.name,
                annotations=self.annotations,
            ),
            spec=k8s.V1PodSpec(
                node_selector=self.node_selector,
                affinity=self.affinity,
                tolerations=self.tolerations,
                init_containers=self.init_containers,
                containers=[
                    k8s.V1Container(
                        image=self.image,
                        name=self.base_container_name,
                        command=self.cmds,
                        ports=self.ports,
                        image_pull_policy=self.image_pull_policy,
                        resources=self.container_resources,
                        volume_mounts=self.volume_mounts,
                        args=self.arguments,
                        env=self.env_vars,
                        env_from=self.env_from,
                        security_context=self.container_security_context,
                        termination_message_policy=self.termination_message_policy,
                    )
                ],