Senior Product Manager, CDP

Primary Duties

• Own the end-to-end product lifecycle for a new AI product, from discovery through launch and iteration
• Define product vision, strategy, and roadmap grounded in deep customer understanding, AI/ML feasibility, and ecommerce CDP architecture
• Architect and drive CDP strategy — including customer identity resolution, behavioral event ingestion, real-time profile unification, audience segmentation, and downstream activation — with enough technical depth to make meaningful build vs. buy decisions
• Define the data contracts and schema design governing how first- and zero-party data flows from Shopify storefronts into unified customer profiles, and how those profiles are consumed by AI models and automation systems
• Partner directly with MLE and prompt engineering to evaluate model capabilities, define evaluation harnesses, set guardrails, and co-design human-in-the-loop experiences — not just review specs, but participate in technical design reviews
• Partner with Engineering to design segmentation and activation frameworks that enable merchants to reach the right customer with the right message at the right moment, powered by real-time CDP data signals
• Design and run rapid experiments to validate hypotheses; define success metrics, instrument tracking, and analyze results yourself where possible
• Write rigorous product specs, success criteria, and evaluation frameworks for AI features — covering accuracy, latency, safety, and user trust
• Collaborate cross-functionally with engineering, design, CSMs, and leadership to ship and iterate
• Develop and maintain a deep competitive understanding of the AI and CDP landscape in ecommerce/SMS
• Serve as the internal and external evangelist for the AI product vision

What We'll Love About You

• 5+ years of product management experience, with 2+ years owning AI/ML-powered products in a hands-on technical capacity
• Strong technical foundation — you have an engineering, data science, or comparable background; you're comfortable in code reviews, data model discussions, and system design conversations