Senior Lead Software Engineering

Pearson•Hoboken, NJ

3d•$240,000 - $260,000•Hybrid

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.

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.

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.