Over two months, this developer built a scalable, data-driven AI and monster framework for the NbcampUnreal/2nd-Team1-Final-Project repository, focusing on rapid content iteration and robust combat systems. They consolidated monster logic into a C++ base class, leveraging data tables for stats and skills, and integrated animation blueprints for natural movement. Their work included implementing reliable collision detection, attack tracing, and UI elements such as health bars and damage widgets, while maintaining code quality through refactoring and cleanup. Using Unreal Engine, Blueprint scripting, and C++, they delivered features that improved gameplay reliability, developer tooling, and the overall maintainability of the project.
June 2025 performance: Delivered data-driven monster design updates, combat reliability improvements, and UI/UX/audio polish across the NbcampUnreal/2nd-Team1-Final-Project. Focused on delivering concrete business value: faster stat tuning via data tables, stable combat experiences, richer boss encounters, and clearer feedback in-game, while maintaining a clean codebase and robust tooling.
June 2025 performance: Delivered data-driven monster design updates, combat reliability improvements, and UI/UX/audio polish across the NbcampUnreal/2nd-Team1-Final-Project. Focused on delivering concrete business value: faster stat tuning via data tables, stable combat experiences, richer boss encounters, and clearer feedback in-game, while maintaining a clean codebase and robust tooling.
May 2025 highlights: Delivered a scalable AI/Monster framework and data-driven monster system, enabling rapid content creation, balance, and QA for dungeon enemies. Key features include AI/Monster scaffolding and asset renaming, dungeon monster assets/animations and test maps, CheatManager integration with test utilities, and consolidation of monster logic into a base class driven by data tables. Introduced desert monsters (Lizardman and Boss Worm) with C++ scaffolding and test spawns, plus ongoing animation/montage improvements and packaging/collision stability fixes. This work provides a robust, data-driven foundation for iterating content with lower risk and faster turnaround times.
May 2025 highlights: Delivered a scalable AI/Monster framework and data-driven monster system, enabling rapid content creation, balance, and QA for dungeon enemies. Key features include AI/Monster scaffolding and asset renaming, dungeon monster assets/animations and test maps, CheatManager integration with test utilities, and consolidation of monster logic into a base class driven by data tables. Introduced desert monsters (Lizardman and Boss Worm) with C++ scaffolding and test spawns, plus ongoing animation/montage improvements and packaging/collision stability fixes. This work provides a robust, data-driven foundation for iterating content with lower risk and faster turnaround times.
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