Job Title

Product Manager – Retail AIPosition Title:Director of Product Management Reports To:Product Owner – Retail AI Focus Area:Retail Planning & Supply Chain Industry Vertical:Retail & Supply ChainExecutive Summary We are seeking a strategic and operationally-mindedDirector of Product Managementto serve as the "Engine Room" of our Product Organization. In this role, you will be the primary partner to the Product Owner, translating high-level vision into a rigorous, executable roadmap. You will sit at the intersection of Engineering, UX, and Go-To-Market teams, ensuring our Data & AI products—specifically ourAgentic Retail AI and Analytics solutions —outpace the competition and deliver seamless value to our Retail clients.Key Responsibilities 1. Strategic Research & Competitive Intelligence Conduct deep-dive competitive analysis to identify market gaps in the Retail planning & Supply chain landscape. Benchmark our AI capabilities (e.g., Agentic workflows, LLM performance) against emerging startups and legacy incumbents. Provide data-driven recommendations to the Product Owner to pivot or double-down on specific features. 2. Roadmap & Lifecycle Operations Own the "Product Operating System"—managing the backlog, sprint priorities, and the translation of business requirements into technical specs. Balance short-term "technical debt" and maintenance with long-term "innovation" bets. Define and track North Star metrics and KPIs for product health and adoption. 3. Cross-Functional Orchestration Engineering:Partner with AI/ML and Data Engineers to ensure feasibility and performance of complex models. UX/Design:Collaborate to simplify complex data outputs into intuitive, "storytelling" dashboards for retail users. PMM & Sales Enablement:Develop the "technical source of truth" for Marketing; create battle cards, demo scripts, and training materials to empower the sales force.Candidate Profile: Qualifications & Skills Core Requirements (Must-Haves): AI/Data Product Background:8+ years in Product Management, with a significant portion dedicated toAI, Machine Learning, or Big Dataproducts. You understand the nuances of the "Model Development Lifecycle." Retail Context:Moderate to deep understanding of theRetail Industry(e.g., inventory management, consumer behavior, omnichannel commerce). Execution Excellence:Proven track record of taking a product from concept to launch, managing complex dependencies across 4+ departments. Technical Fluency:Ability to engage in deep-technical discussions with AI researchers while translating the "so what" for business stakeholders. Preferred Qualifications (Nice-to-Haves): Customer-Facing Experience:Comfort leading "Alpha/Beta" feedback sessions with Tier-1 Retail clients. Analyst Relations:Experience managing briefings with industry analysts (e.g., Gartner, Forrester) to influence Magic Quadrant/Wave positioning. Strategic Growth:Experience in a high-growth "Services-to-Product" transition environment.