Cybersecurity demands creativity, persistence, and sharp pattern recognition—strengths frequently reported among neurodivergent people (e.g., autism, ADHD, dyslexia). Yet AI-driven hiring pipelines can systematically disadvantage neurodivergent applicants by misreading communication styles or valuing narrow proxies of “fit.” Meanwhile, workforce demand is surging; sector reports and commentary argue that neurodiversity is both under-represented and strategically valuable to security teams, but progress is uneven without targeted educational interventions. We present a curricular module that simultaneously (a) centers neurodiversity as a strength in the cybersecurity workforce and (b) trains students to audit and redesign AI hiring systems using open-source fairness and explainability toolkits (AIF360 and SHAP). Students run endto-end labs, evaluate trade-offs between performance and equity, and propose inclusive pipeline redesigns aligned with emerging policy guidance on AI and disability.