Senior Product Manager | Applied AI

We are growing a product-management team that runs AI-powered products and applies AI across the whole product lifecycle. As a Senior Product Manager | Applied AI, you will own the vision, strategy, roadmap and delivery of one or more products — at least one of them AI-powered — while using AI day-to-day to work faster and make sharper decisions and mentoring other Product Managers as you do.

What "Applied AI" means here. This is a product role, not an engineering role. We expect confident, practical command of AI as a product manager — using it across the lifecycle and shaping AI-powered features — not the ability to build, train or tune machine-learning models as an ML engineer or data scientist would.

Req# The recruiting efforts for this position are intended to fill an existing vacancy for a new position.

Responsibilities Own the vision, strategy, roadmap and end-to-end delivery of one or more products, including at least one that is AI-powered

Define requirements and use cases for AI features, treating them as probabilistic products — scoping data and use-case fit, and setting evaluation criteria, quality bars, guardrails and human-in-the-loop review as acceptance criteria

Identify where AI can improve the product, the customer experience, internal processes or business outcomes — and build and size the case for itUse AI tools productively and with discipline across discovery, research synthesis, analysis, documentation, user stories, prototyping and planning — verifying outputs before relying on them Prioritise features, own the backlog and manage release cycles, using AI-assisted analysis to support (not replace) your decisions

Manage the full product lifecycle, including the added considerations of AI features — model/version changes, quality drift and human oversight

Work closely with engineering, data, design and AI/ML teams, translating product intent into requirements they can act on and their constraints into product decisions

Set realistic expectations with clients and stakeholders about what AI can and cannot do, and communicate benefits, limitations and risks in plain language

Mentor Product Managers and raise the team's practical AI capability by example

Requirements5+ years in Product Management, having managed one or more products end-to-end, including post-launch maintenance and support

Launched more than one product (or key capability) to market, with at least one experience delivering or materially improving an AI-powered product or feature (e.g., GenAI, ML, recommendations, search or automation)
Solid ownership of product strategy, vision and roadmap; market analysis and product visioning — including identifying and justifying where AI adds value

Experience owning backlogs, cross-product dependencies and release cycles, and managing product lifecycle and support models

Familiarity with product profitability, competitive positioning and pricing — including the cost, latency and quality trade-offs that shape AI-feature economics

Expertise across multiple (3+) business domains, able to act as a business-domain SMEWorking AI literacy — what current AI (including GenAI/LLMs) can and cannot do reliably, common patterns and typical failure modes — enough to make sound product decisions and hold credible conversations with technical teams. Deep model-building knowledge is not required

Able to influence stakeholders up to and including VP level, and to lead all critical aspects of a product launch

Able to lead a team of Product Owners and/or Product Managers across a product line or family, guiding them through the full lifecycle

Raises the team's practical AI proficiency — sharing verified ways of working and coaching on requirements and evaluation criteria for AI features

Practical,…