Pearson

Compensation

Full Description

About the position As Head of Engineering / Senior Lead, Emerging Technology & Software Engineering, you will own the engineering vision and execution for AI-driven experiences within the Pearson Learning Studio (XL+) platform — an AI-first courseware ecosystem layering advanced intelligence on top of a modernized, domain-driven services architecture. You will lead a global, metrics-driven organization of ~100 engineers and data scientists across multiple scrum teams, shaping the delivery of next-generation learning experiences including Student AI Mentor, Personalized Insights & Recommendations, and analytics powered by Learner Models, Knowledge Graphs, and shared platform services. This role is for a grounded, low-ego leader who wins through trust, clarity, and execution — someone who builds strong teams, partners deeply with product and business leaders, and consistently turns emerging technology into real-world impact for students and educators. Responsibilities • Define and execute the AI and GenAI engineering strategy aligned to Pearson’s learning outcomes and business goals. • Lead the design, development, and deployment of scalable AI solutions including conversational tutoring, personalization engines, and intelligent insights across the XL+ platform. • Drive responsible adoption of Generative AI, LLMs, knowledge graphs, and learner modeling frameworks to improve engagement, retention, and learning efficacy. • Build and mentor a high-performing, psychologically safe engineering culture grounded in humility, ownership, curiosity, and results. • Lead multiple distributed scrum teams, developing future leaders and ensuring consistent execution excellence across geographies. • Foster collaboration across product, UX, analytics, content, and commercial teams — removing silos and aligning everyone to shared outcomes. • Establish clear success metrics across delivery velocity, reliability, quality, adoption, and learner outcomes. • Create strong operating rhythms using OKRs, agile metrics, experimentation frameworks, and business impact KPIs. • Translate strategy into execution plans that consistently deliver high-quality outcomes at scale. • Define standards for architecture, data governance, model lifecycle management, and AI safety. • Ensure all solutions meet strict standards for accuracy, fairness, compliance, privacy, security, and reproducibility. • Continuously improve engineering productivity through automation, MLOps/LLMOps, CI/CD pipelines, and modern cloud practices. • Serve as a trusted partner to senior business, product, and academic leaders — translating technical complexity into clear, actionable decisions. • Communicate insights and risks with clarity, empathy, and credibility. Requirements • Deep expertise in Artificial Intelligence, Machine Learning, Generative AI, LLMs, and AI product engineering. • Strong background in software engineering, data engineering, analytics platforms, and Python-based ecosystems. • Proven success leading large, metrics-driven teams in high-growth, complex environments. • Exceptional interpersonal skills — able to inspire, listen, influence, and build trust without ego. • Strong systems thinking, with the ability to connect learner needs, business strategy, and technology architecture. • Track record of applying emerging technologies pragmatically — turning innovation into shipped products. • Master’s or PhD in Computer Science, Data Science, Engineering, or a related field. • 10+ years in software engineering, emerging technologies, analytics, and GenAI, including 5+ years leading organizations of 50+ engineers across multiple agile teams. • Demonstrated experience delivering AI-powered platforms in education, SaaS, or consumer-scale products. • History of building teams that outperform on delivery, quality, and culture — not through command-and-control, but through clarity, trust, and accountability.