Charles Alaras enhanced build reproducibility and caching for Intel-tensorflow/tensorflow and Intel-tensorflow/xla by developing more granular HLO module fingerprinting. He introduced custom field support in the fingerprinting process, allowing module attributes to be captured in greater detail and enabling deterministic builds across environments. This work required coordinated updates to both repositories, ensuring consistent fingerprint semantics and reducing unnecessary rebuilds. Using C++ and leveraging expertise in build systems and compiler development, Charles focused on feature enhancements rather than bug fixes. The depth of his contributions established a stronger foundation for reliable optimization and deployment workflows in low-level software engineering contexts.