• Own the generation and quality of front-end code produced through AI-assisted development workflows. • Define and maintain clear acceptance criteria and test cases before implementation begins, ensuring a test-driven development approach. • Review, refine, and approve AI-generated front-end code to ensure it meets product requirements, engineering standards, and long-term maintainability goals. • Provide structured guidance and constraints to AI systems so generated code aligns with established front-end architecture and patterns. • Write code as necessary to fill in gaps and bridge the last mile. • Identify gaps, edge cases, and failure modes in AI-generated solutions and address them through improved tests, specifications, or guidance. • Ensure front-end implementations meet accessibility, performance, and usability expectations. • Act as the final quality checkpoint for front-end work prior to merge or release. • Continuously improve AI-assisted development practices based on observed outcomes and quality trends.