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Job Description & How to Apply Below
Product Manager – Retail AI
Position Title:
Director of Product Management
Reports To:
Product Owner – Retail AI
Focus Area: Retail Planning & Supply Chain
Industry Vertical: Retail & Supply Chain
Executive Summary
We are seeking a strategic and operationally-minded Director of Product Management to 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 our Agentic 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 to AI, Machine Learning, or Big Data products. You understand the nuances of the "Model Development Lifecycle."
Retail Context: Moderate to deep understanding of the Retail 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.
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