Sr Product ManagerSkip to main contentWe use cookies (or similar technologies) to personalize content and ads, to provide social media features and to analyse our traffic. By clicking "Accept ", you agree to this and the sharing of information (What data we collect) about your use of our site with our affiliates & partners. Please find out more

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e of cookies.#Sr Product Manager page is loaded## Sr Product ManagerApplylocations: Tlaquepaque, Jalisco, Mexico: Sant Cugat del Valles, Barcelona, Spaintime type: Full timeposted on: Posted Todaytime left to apply: End Date: September 11, 2026 (17 days left to apply)job requisition id: 3167659Sr Product ManagerDescription -# Product Manager – AI-Powered Seller Recommendations## Role OverviewWe are looking for a strategic, customer-obsessed, and data-driven Product Manager to define and build an intelligent recommendation product that helps our internal sales teams identify which products, solutions, and offers are most relevant for each customer.
This product will bring together customer signals, product usage, purchase history, account characteristics, seller activity, market insights, and business priorities to generate actionable recommendations for sellers.
The product should help sellers answer questions such as:
* What should I recommend to this customer next?
* Which products or solutions are most relevant to this customer's needs?
* Which customer signals indicate a potential opportunity?
* Why is a particular product being recommended?
* What is the best next action for this account?
* Which opportunities should I prioritize across my customer portfolio?The Product Manager will own the product vision, strategy, roadmap, business case, and execution for this capability, working at the intersection of AI/ML, data, CRM, sales enablement, enterprise software,



and commercial strategy.
This role requires a unique combination of product management, structured problem solving, commercial acumen, analytical thinking, and the ability to influence senior stakeholders across a complex organization.
The idóneo candidate will be comfortable moving between strategic questions, such as defining the future of AI-powered selling, and detailed product decisions around recommendation logic, ranking, explainability, seller experience, experimentation, and measurement.##

Key Responsibilities
### Product Vision & Strategy
* Define the long-term vision and product strategy for an intelligent next-best-product and next-best-action recommendation platform for internal sellers.
* Develop a deep understanding of seller, customer, and business needs and translate them into scalable product opportunities.
* Define the core problems the product will solve and establish clear product principles and priorities.
* Build and maintain a multi-year product roadmap balancing customer value, seller productivity, commercial impact, technical feasibility, and company strategy.
* Identify opportunities to evolve the solution from rules-based recommendations toward predictive, personalized, and AI-powered recommendations.
* Define how the product fits within the broader sales, CRM, customer intelligence, and AI ecosystem.




* Evaluate strategic opportunities and trade-offs using structured business cases, quantitative analysis, customer insights, and competitive benchmarks.### Seller & Customer Experience
* Develop a deep understanding of seller workflows through interviews, field observation, telemetry, experimentation, and qualitative research.
* Design experiences that surface the right recommendation, to the right seller, for the right customer, at the right time.
* Ensure recommendations are relevant, actionable, explainable, and easy for sellers to incorporate into customer conversations.
* Define how recommendations should be presented, prioritized, grouped, and integrated into existing seller workflows.
* Create mechanisms that allow sellers to understand the signals and rationale behind each recommendation.
* Design seller feedback mechanisms that capture whether recommendations are accepted, rejected, dismissed, acted upon, or considered irrelevant.
* Reduce seller effort by integrating recommendations directly into CRM, account planning, opportunity management, and seller productivity tools.
* Ensure the product ultimately optimizes for customer relevance and customer value, not simply product promotion.### AI, Data & Recommendation Systems
* Partner closely with data science, machine learning, engineering, and analytics teams to define the recommendation architecture and product requirements.
* Identify and prioritize the customer and commercial signals required to generate high-quality recommendations.
* Define requirements for recommendation eligibility, scoring, ranking, personalization, confidence, explainability, and suppression.
* Determine how signals such as product usage, installed base, purchase history, customer profile, industry, intent, engagement, suppo

📌 Sr Product Manager (San Pedro Tlaquepaque)
🏢 Hewlett Packard
📍 San Pedro Tlaquepaque