Forward-Deployed AI Product Owner for Education

LearningMate; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

LearningMate is seeking a Forward Deployed AI Product Owner to blend consulting, product leadership, and AI strategy for education customers. You will embed with schools, publishers, and learning organizations to transform workflows into AI-native solutions.

You will lead discovery workshops, define MVPs, write PRDs, and drive AI-first SDLC across discovery, architecture, governance, development, testing, deployment, and optimization.

Qualifications

• 8+ years in Product Management, Product Ownership, or Solution Architecture
• Experience working directly with customers
• Experience in Agile environments
• Experience with AI-enabled products
• Experience within Education, Publishing, Learning Platforms, or EdTech

Responsibilities

• Partner directly with education organizations, publishers, universities, K-12 districts, and learning companies.
• Lead discovery workshops to understand business objectives, pain points, workflows, and data ecosystems.
• Map current-state and future-state processes.
• Translate ambiguous business problems into product opportunities.
• Build trusted relationships with executive stakeholders.
• Own AI products from concept through deployment.
• Define product vision and roadmap.
• Create Product Requirement Documents (PRDs).
• Write detailed user stories and acceptance criteria.
• Lead products through an AI-native SDLC, including discovery, AI-assisted architecture, development, testing, evaluation, deployment, and optimization.

Skills

Executive communication

Workshop facilitation

Process mapping

Requirements gathering

Change management

Job description

LearningMate is seeking a Forward Deployed AI Product Owner to blend consulting, product leadership, and AI strategy for education customers. You will embed with schools, publishers, and learning organizations to transform workflows into AI-native solutions.

You will lead discovery workshops, define MVPs, write PRDs, and drive AI-first SDLC across discovery, architecture, governance, development, testing, deployment, and optimization.