Server Side Encryption using KMS Key failing for validate_s3_path_exists

**PySDK Version**
- [ ] PySDK V2 (2.x)
- [x] PySDK V3 (3.x)

**Describe the bug**
While running `sagemaker.train.sft_trainer.SFTTrainer`, internally, the function `sagemaker.train.common_utils.finetune_utils._validate_s3_path_exists` is called but if the s3 bucket referred has SSE (Server Side Encryption) enabled and the path doesn't exist, `s3.put_object` fails.

**To reproduce**
* Add SSE using kms key to your target s3 bucket for SFT job
* For any dataset, try running SFTTrainer job, it fails saying access denied.

**Expected behavior**
Since kms_key_id is an accepted parameter in SFTTrainer, `_validate_s3_path_exists` should succeed and proceed to launch the job. Note that after the actual training is done, the subsequent `put_object` for model files does not fail.

**System information**
A description of your system. Please provide:
- **SageMaker Python SDK version**: 3.12.0
- **Python version**: 3.12
- **CPU or GPU**: CPU
- **Custom Docker image (Y/N)**: N

**Additional context**
Add any other context about the problem here.

Start in sagemaker/train/common_utils/finetune_utils.py at _validate_s3_path_exists, then trace its call from sagemaker.train.sft_trainer.SFTTrainer. Reproduce the missing-path case with an SSE-KMS-encrypted S3 bucket and verify that validation succeeds and the SFTTrainer job proceeds without access denied.

Written by the indexing model from the issue text.