Worked on the MegaMek/mekhq repository to implement a doctor education level boost for non-combat roles, enhancing the accuracy of medical personnel progression and staffing readiness modeling. The solution refactored the initial education calculation to use the greater of current experience or a veteran threshold, propagating effective experience throughout the process for improved balance. Delivered via Java-based backend development, the work included stability improvements for pull request discovery tooling and leveraged AI-assisted code quality tools. These changes provided a more predictable framework for clinician readiness and established a foundation for future role-specific tuning, demonstrating depth in experience-based logic and backend refactoring.