Principal, Product Management

Pearson•Hoboken, NJ

About The Position

Pearson is the world’s leading learning company. We help learners of all ages make measurable progress in their lives through education. Our digital products, platforms, and services empower millions of learners every day. We combine learning science, innovative technology, and deep expertise to create engaging, accessible learning experiences that support personal and professional growth. Pearson is seeking a Principal Product Manager to be a hands-on leader to drive the strategic evolution of our AI-powered learning ecosystem. As we scale our Generative AI capabilities, we need a seasoned product manager to rapidly accelerate the advancement of the feature set and the corresponding value provided to customers. This role doesn’t just define the destination; it involves rolling up the sleeves and bringing the vision to fruition.

Requirements

5-8 years of software product management experience, with a proven track record of launching and scaling successful digital products.
Deep hands-on experience with LLMs, prompt engineering, and at least one year of experience shipping production-grade Generative AI features.
Significant familiarity with Retrieval Augmented Generation (RAG), vector databases, agentic workflows, prompt optimization, and model evaluation.
Proven ability to lead through influence, managing complex stakeholder environments and cross functional dependencies.
Clear and concise communication skills with the ability to collaborate effectively.

Nice To Haves

Experience in EdTech or a highly regulated industry where "hallucination" risks require sophisticated mitigation strategies.
Strong analytical background, experience with data analytics platforms.
Working knowledge of agile development practices.

Responsibilities

Lead the end-to-end feature development lifecycle for AI-based product features – from discovery and requirements to launch and optimization.
Write, test, and refine prompts and agent behaviors within Pearson’s agentic AI framework.
Collaborate with global multifunctional teams – includes partnering with engineering to make trade-off decisions on latency, token cost, and accuracy, and with data and QA teams to validate model outputs.
Establish rigorous model evaluation standards to ensure the safety, accuracy, and pedagogical integrity of agent outputs.
Deeply analyze user behavior data and A/B test results to guide feature decisions.
Conduct competitive research and stay informed on emerging trends in GenAI and EdTech.
Serve as a team resource on LLM capabilities, agent & prompt design, and best practices in applied GenAI.
Contribute to Pearson’s responsible AI guidelines, including evaluation, monitoring, ethical data use, and transparency.
Identify opportunities to use AI to enhance product development and operational efficiency.