AI-driven recruitment systems offer potential benefits in improving hiring efficiency and reach. However, without explicit attention to inclusivity, these systems risk perpetuating historical biases and reinforcing systemic inequalities. While ethical guidelines for inclusive AI exist, organisations face challenges in operationalising them, particularly in complex, real-world settings like online employment platforms. This paper investigates how inclusive design principles, grounded in diversity and inclusion guidelines, can be translated into requirements for AI recruitment systems. We partnered with SEEK, a leading employment marketplace in the Asia-Pacific region, to conduct a co-design workshop focused on identifying and contextualising inclusivity requirements from AI-based hiring use cases. Using requirements engineering techniques of user stories, personas, and stakeholder reflection, we explored two use cases and conducted follow-up interviews six months later to evaluate the impact and sustainability of these efforts. Our findings reveal challenges in aligning inclusivity with business priorities, navigating trade-offs, and addressing data limitations. We present industry-informed lessons on how requirements engineering can support the operationalisation of inclusive AI principles, offering guidance for practitioners aiming to embed diversity and inclusion principles in AI systems. This work contributes to integrating ethical design into AI development lifecycles through stakeholder-driven requirements processes.