We are looking for a product leader to run a portfolio that includes AI-powered products and to own how our Product Management team applies AI — the strategy, standards, investment decisions, governance and team capability. You will lead and develop a team of Product Managers, own product strategy and P&L across the portfolio, and raise the organization's product-AI capability. What "Applied AI" means at Director level. The emphasis shifts from doing the hands-on AI work to judging it, funding the right AI bets and setting the guardrails. This is a product-leadership role — not an engineering, data-science or AI-research role. You set direction and standards for the specialists who build. Req# 1100335863 Responsibilities Lead and develop a team of Product Managers running a portfolio that includes AI-powered products; own product strategy, vision and P&L across that portfolio Set an AI-informed product strategy — where AI creates durable advantage, where it is commoditizing, and how to sequence the roadmap against advancing AI capability Make build / buy / partner and investment decisions for AI capabilities; own AI business cases and ROI; fund the right experiments and know when to stop them Own AI-feature economics and lifecycle across the portfolio — cost, latency, unit economics, pricing, and model-lifecycle decisions (drift, versioning, vendor change) Set the standards, operating model and review gates for how the team builds AI features and uses AI in its own work, so quality and responsibility are consistent Own responsible-AI governance — privacy, bias, security, transparency, human oversight, audit trails, incident response, and applicable regulation (e.g., EU AI Act) and sector rules Raise the team's AI capability through coaching, playbooks, shared prompt/agent libraries and an AI component in the hiring bar; advise business units or clients on adoption Direct effective collaboration across product, engineering, data, design and AI/ML teams, keeping product intent, constraints and accountability clear Represent the organization credibly on its AI product strategy with senior clients — setting realistic expectations rather than over-promising Requirements 7+ years in Product Management, having managed products, product lines/families and/or groups, with experience leading PM/PO teams; developed and/or launched 3+ products to market, including AI-powered products or capabilities Ownership of product vision, roadmap and P&L, and of strategic roadmap alignment across a portfolio Portfolio analysis and strategy formulation; prioritizing spend by ROI and supporting financial models — including AI business cases and build/buy/partner decisions Track record aligning product strategy with new technologies, assessing and adopting emerging AI capabilities responsibly SME across multiple (3+) business domains; deep grasp of consumer trends, technological disruption and competitive factors — including how AI is reshaping the domain AI literacy sufficient to lead — understands AI concepts, capabilities and limitations well enough to make sound portfolio and investment decisions and to challenge technical proposals credibly. ML-engineering / data-science depth is not required Able to shape company product strategy, convey difficult messages to senior stakeholders and own key initiatives and business KPIs Leads, develops and champions a team of Product Managers across a multi-product portfolio; identifies and plans for performance improvement Sets the operating model for how the team applies AI, and raises its proficiency through enablement, coaching and a clear hiring bar AI-informed product/portfolio strategy — advantage vs commoditization, build/buy/ partner, AI business cases and ROI, roadmap sequencing against AI capability Responsible-AI governance across the portfolio — privacy, bias, security, transparency, human oversight, audit trails/incident response and relevant regulation Ownership of AI-feature economics and lifecycle — cost, latency, unit economics, pricing, drift/versioning/vendor decisions Setting AI standards and review gates for how the team builds AI features and uses AI Raising team AI capability — enablement, coaching, playbooks, shared tooling, hiring bar Ability to evaluate AI outputs, prototypes and technical proposals and fund the right bets Working AI literacy — concepts, capabilities and limitations sufficient to lead and challenge Continued practical use of AI in own work and adaptability as AI evolves Ability to direct effective collaboration across engineering, data, design and AI/ML teams Not required: building, training, fine-tuning or deploying ML models; data-science, MLOps or AI-research depth. The Director sets direction and standards for the specialists who do this work Nice to have Deep hands-on AI prototyping or feature-building (valued, but expected to plateau here — it is the Senior PM / IC strength; the Director's job is to judge and fund, not build) External thought leadership on AI product management (talks, publications, community) Direct experience standing up an AI governance or enablement program at organization scale
