AI/Product Manager

Roles and Responsibilities

Product Vision & Strategy: Define and communicate the long-term vision and

strategy for company AI and data product portfolio, ensuring alignment with overall

company goals.

Roadmap Management: Build, prioritize, and manage the product roadmap,

balancing short-term business needs with long-term technological innovation.

P&L & Commercial Strategy: Manage the P&L for AI product lines. Develop pricing

models, go-to-market strategies, and business cases to justify investments and

maximize ROI.

Senior Stakeholder Management: Act as the primary point of contact and advisor for

Senior Executive Stakeholders. You will manage expectations, provide strategic

updates, and influence decision-making by demonstrating the business impact of AI

initiatives.

Cross-Functional Orchestration: Serve as the central hub connecting diverse

teams. You will facilitate collaboration and ensure seamless communication between

AI Research, Data Science, Software Engineering, and Business Units to deliver

unified product solutions.

Market Intelligence: Conduct deep-dive market research into trends, competitor AI

offerings, and emerging technologies (Agentic AI, GenAI, LLMs, Predictive Analytics)

to identify new product opportunities.

User-Centric Design: Collaborate with UX and data teams to ensure AI products are

intuitive, actionable, and effectively integrated into the daily workflows of retail

operators.

Outcome Delivery: Define and track key performance indicators (KPIs) for product

success, focusing on adoption rates, revenue growth, and measurable business

impact (e.g., uplift in basket size or inventory efficiency).

Lifecycle Management: Oversee the entire product lifecycle from conceptualization

and PoCs to full-scale production and continuous optimization.

Qualifications

Educational Background: Bachelor's or Master's degree in Data Science, Computer

Science, Engineering, or an MBA with a strong technical focus.

Experience: Minimum 7 years of professional experience, with at least 3 years in

Product Management specifically focused on Data or AI products.

Technical Literacy: Strong foundational knowledge of AI/ML concepts (LLMs, RAG,

Predictive Modeling, Recommendation Engines) and Software Development

Lifecycles (SDLC) to effectively translate business needs into technical requirements.

Business Acumen: Demonstrated experience managing a product P&L, including

budget allocation, financial forecasting, and commercial negotiation.

Elite Communication & Management: Exceptional ability to navigate both the

boardroom and the engineering floor. You must be comfortable discussing model

performance with Data Scientists, architecture with Software Engineers, and P&L with

Senior Executives.

Problem-Solving: Data-driven mindset with the ability to use analytics to identify

product gaps and validate hypotheses.