### 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)

if self.pod:
            pod = self.pod
            kwargs = {
                "name": pod.metadata.name,
                "namespace": pod.metadata.namespace,
            }
            if self.termination_grace_period is not None:
                kwargs.update(grace_period_seconds=self.termination_grace_period)
            self.client.delete_namespaced_pod(**kwargs)
    def build_pod_request_obj(self, context: Context | None = None) -> k8s.V1Pod:
        """
        Returns V1Pod object based on pod template file, full pod spec, and other operator parameters.
        The V1Pod attributes are derived (in order of precedence) from operator params, full pod spec, pod
        template file.
        """
        self.log.debug("Creating pod for KubernetesPodOperator task %s", self.task_id)
        if self.pod_template_file:
            self.log.debug("Pod template file found, will parse for base pod")
            pod_template = pod_generator.PodGenerator.deserialize_model_file(self.pod_template_file)
            if self.full_pod_spec:
                pod_template = PodGenerator.reconcile_pods(pod_template, self.full_pod_spec)
        elif self.full_pod_spec:
            pod_template = self.full_pod_spec
        else:
            pod_template = k8s.V1Pod(metadata=k8s.V1ObjectMeta())