Developed PipelineVariable support for ModelTrainer fields in the aws/sagemaker-python-sdk, enabling dynamic parameterization in SageMaker Pipelines through ParameterString integration. The work involved extending typing with StrPipeVar and aligning field handling with V3 patterns to support migration from V2, enhancing pipeline reusability and deployment flexibility. Comprehensive unit testing was implemented in Python, adding nine new tests to cover acceptance, regression, and invalid type scenarios, ensuring robust validation and zero regressions. Addressed logging edge cases to prevent TypeError during string conversion of PipelineVariable objects. Collaborated cross-team to co-author the change, emphasizing code quality and maintainability in a full stack context.