Lead Specialist, Product Program Manager

**Lead Specialist, Product Program Manager (AI)** **Role Overview** The **Lead Specialist Product Program Manager (AI)** is responsible for leading cross‑functional teams to deliver highly complex, AI‑driven programs that bring AI technologies into production and are critical to business success. This role sits on Pearson’s Expert track and requires deep technical and domain expertise, exceptional execution skills, and the ability to independently drive significant initiatives from concept through delivery. The individual in this role will be trusted to deliver outcomes across large, interdependent AI programs, serve as a technical advisor to peers and leaders, and mentor other program managers, while remaining hands‑on in execution rather than people management. This role partners closely with Product Managers and other leaders to ensure AI product and platform initiatives are effectively planned, orchestrated, and delivered, owning execution across complex, multi‑team programs. This role supports programs centered entirely on AI technologies in production, including machine learning systems, data platforms, AI‑enabled student and teacher experiences, and responsible AI practices. Programs may include initiatives such as the AI Teacher Assistant, AI Student Tutor, and foundational AI platforms that enable AI‑powered capabilities across Pearson Virtual Schools. **Key Responsibilities** * Lead and deliver mission‑critical, AI‑centric programs with significant technical complexity, cross‑portfolio dependencies, and organizational visibility, owning outcomes end‑to‑end from planning through execution. * Develop, maintain, and execute integrated program plans that translate AI product and platform strategy into clear milestones, timelines, and success metrics across research, development, deployment, and operationalization. * Drive execution across multiple, interdependent workstreams, ensuring timely delivery, quality outcomes, and alignment with business objectives in highly ambiguous environments. * Identify, assess, and mitigate program‑level risks and issues related to AI development, including data readiness, model performance, integration challenges, scalability, compliance, and ethical considerations. * Serve as the primary point of accountability for AI program outcomes, proactively removing blockers and facilitating effective cross‑team collaboration to manage dependencies. * Act as the program management authority for AI programs, demonstrating fluency in AI/ML lifecycles (including experimentation, model iteration, and production support) and partnering closely with engineering, data science, product, learning science, security, legal, and operations teams. * Support discovery and delivery alignment by ensuring experimentation, validation, and iteration are reflected appropriately in program plans and timelines. * Apply appropriate Agile, Scrum, Kanban, and hybrid delivery methodologies to AI initiatives where experimentation, it