Product Manager

Product Manager at Pearson

At Pearson, we’re committed to a world that’s always learning and to our talented team who makes it all possible. From bringing lectures vividly to life to turning textbooks into laptop lessons, we are always reexamining the way people learn best, whether it’s one child in our own backyard or an education community across the globe.

We are bold thinkers and standout innovators who motivate each other to explore new frontiers in an environment that supports and inspires us to always be better. By pushing the boundaries of technology — and each other to surpass these boundaries — we create seeds of learning that become the catalyst for the world’s innovations, personal and global, large and small.

Our Direct To Consumer team at Pearson has an excellent opportunity for a Product Manager to join our growing team. Working in a small-team environment, you will have a unique opportunity to play a leading role in designing and developing web-based delivery applications for the company’s line of spoken assessment products.

To be successful in this essential role, you must have the desire and ability to learn new techniques and share your knowledge. You need to demonstrate a passion for software development, software craftsmanship, and ability to perform in a quick-pace, dynamic work environment! Tremendous growth opportunity!

Job Summary

Pearson is seeking a 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 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.

Key Responsibilities

• AI Product Development & Execution
  • 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.
• Insights, Research & Data-Informed Decisions
  • 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.
  • Identify opportunities to use AI to enhance product development and operational efficiency.

Required Qualifications

• Experience: 3-5 years of software product management experience, with a proven track record of launching and scaling successful digital products.
• AI Expertise: Deep hands-on experience with LLMs, prompt engineering, and at least one year of experience shipping production-grade Generative AI features.
• Technical Depth: Significant familiarity with Retrieval Augmented Generation (RAG), vector databases, agentic workflows, prompt optimization, and model evaluation.
• Communication: Clear and concise communication skills with the ability to collaborate effectively.

Preferred Qualifications

• 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.

Who We Are

At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. We are the world's lifelong learning company. For us, learning isn't just what we do. It's who we are. To learn more: We are Pearson.

Key skills/competency

• Product Management
• AI Product Development
• Generative AI
• LLMs (Large Language Models)
• Prompt Engineering
• Retrieval Augmented Generation (RAG)
• Vector Databases
• Agile Development
• Data Analytics
• User Behavior Analysis