PIM AI Product Manager

Description

Role Overview

We are seeking an experienced PIM AI Product Manager to lead the definition and implementation of a modern Product Information Management capability. This consultant will collaborate with various stakeholders across business, technology, digital commerce, merchandising, and data to establish a clear PIM strategy, define the implementation roadmap, and guide the organization through solution selection and delivery. The role will also identify practical opportunities to leverage artificial intelligence to enhance product-data quality, automate manual processes, enrich product content, and accelerate time to market.

Key Responsibilities

• Product Strategy and Roadmap
  • Assess current product-information processes, systems, data flows, governance practices, and operational pain points.
  • Define the target vision and product strategy for a modern enterprise PIM capability.
  • Develop a phased implementation roadmap aligned with business priorities, technical dependencies, organizational readiness, and measurable outcomes.
  • Translate business needs into product requirements, user stories, acceptance criteria, and prioritized delivery backlogs.
  • Establish a clear product operating model, including decision rights, ownership, governance, and stakeholder responsibilities.
  • Define success measures covering data quality, productivity, adoption, time to market, and digital-channel performance.
• PIM Solution Definition and Implementation
  • Lead or support the evaluation and selection of an appropriate PIM solution.
  • Define functional, technical, integration, security, scalability, and usability requirements.
  • Guide the design and implementation of product onboarding, enrichment, approval, publishing, and maintenance workflows.
  • Ensure the solution supports current requirements while providing a scalable foundation for future channels, product categories, and business capabilities.
  • Partner with implementation teams and vendors to manage scope, clarify requirements, resolve issues, and maintain delivery alignment.
  • Support testing, data migration, deployment planning, and post-implementation stabilization.
  • Identify delivery risks, dependencies, and capability gaps, and recommend practical mitigation strategies.
• Product Data Management and Governance
  • Define the product-data model, including attributes, categories, hierarchies, relationships, variants, and digital assets.
  • Establish standards for product taxonomy, metadata, naming conventions, classification, and data ownership.
  • Design governance processes that improve the accuracy, completeness, consistency, and timeliness of product information.
  • Clarify the responsibilities of data owners, data stewards, content contributors, approvers, and downstream consumers.
  • Define data-quality rules, validation controls, exception-management processes, and performance indicators.
  • Develop scalable processes for creating, enriching, reviewing, approving, publishing, and retiring product information.
• AI-Enabled Product Information Capabilities
  • Identify and prioritize AI use cases that deliver measurable value within the product-information lifecycle.
  • Evaluate opportunities such as automated product classification, attribute extraction, content generation, translation, enrichment, deduplication, data-quality validation, anomaly detection, and intelligent search.
  • Assess AI opportunities based on business value, feasibility, data readiness, implementation effort, risk, and expected return.
  • Define appropriate human-review and approval controls for AI-generated or AI-enriched product information.
  • Ensure proposed AI capabilities account for accuracy, traceability, privacy, security, intellectual-property considerations, and responsible-use requirements.
  • Translate promising AI concepts into practical pilots, implementation plans, and measurable business outcomes.
  • Monitor emerging AI and PIM capabilities and recommend relevant enhancements to the roadmap.
• Stakeholder and Change Leadership
  • Facilitate discovery workshops with business, technical, operational, and digital-commerce stakeholders.
  • Build alignment across teams with different requirements, priorities, and levels of PIM maturity.
  • Communicate complex product-data and AI concepts in clear business language.
  • Prepare decision materials, recommendations, roadmaps, and progress updates for senior stakeholders.
  • Support organizational readiness, process adoption, training, and change-management activities.
  • Promote consistent product-data practices across business units, systems, and sales channels.
  • Transfer knowledge to internal product owners, administrators, data stewards, and operational teams.

Required Qualifications

• Demonstrated experience leading PIM strategy, product management, implementation, or transformation initiatives.
• Strong understanding of PIM concepts, platforms, operating models, workflows, and implementation practices.
• Experience defining product-information taxonomies, metadata standards, attribute models, category hierarchies, and data-governance processes.
• Experience translating business requirements into product roadmaps, solution requirements, user stories, and implementation priorities.
• Strong understanding of product-data quality, data stewardship, lifecycle management, and governance.
• Experience supporting or leading integrations between PIM platforms and related enterprise systems, such as ERP, e-commerce, digital asset management, content management, supplier, marketplace, or analytics platforms.
• Knowledge of digital-commerce operations and the role of high-quality product information in customer experience and channel performance.
• Practical understanding of AI, machine learning, or generative AI applications relevant to product-information management.
• Experience assessing and prioritizing opportunities based on business value, feasibility, risk, and organizational readiness.
• Strong stakeholder-management, workshop-facilitation, communication, and executive-presentation skills.
• Ability to work effectively across business, data, technology, operations, and vendor teams.
• Demonstrated ability to operate in ambiguous environments and turn broad objectives into actionable plans.

Preferred Qualifications

• Experience selecting, implementing, or optimizing one or more commercial PIM platforms.
• Experience with retail, consumer products, digital commerce, merchandising, distribution, or other product-intensive environments.
• Familiarity with master data management, data integration, data architecture, APIs, and cloud-based enterprise platforms.
• Experience with product-content syndication, supplier-data onboarding, digital asset management, or omnichannel publishing.
• Experience implementing AI-assisted product-content or data-quality capabilities.
• Understanding of responsible AI, model governance, privacy, security, and human-in-the-loop controls.
• Experience managing implementation partners, software vendors, or multidisciplinary delivery teams.
• Relevant certifications in product management, agile delivery, data management, enterprise architecture, or a leading PIM platform.

Core Competencies

• Product strategy and roadmap development
• PIM implementation and optimization
• Product-data modelling and governance
• Taxonomy and metadata design
• AI opportunity identification and prioritization
• Digital-commerce enablement
• Requirements definition and backlog management
• Business-process analysis and redesign
• Data-quality management
• Systems-integration awareness
• Stakeholder alignment and facilitation
• Vendor and delivery management
• Change leadership and knowledge transfer
• Clear written and verbal communication

Expected Deliverables

• Current-state assessment and capability-gap analysis
• PIM vision, strategy, and target-state definition
• Prioritized business requirements and use cases
• Product taxonomy, metadata, and data-model recommendations
• Product-data governance framework
• AI opportunity assessment and prioritized use-case portfolio
• PIM platform evaluation or selection criteria
• Phased implementation roadmap
• Product backlog, user stories, and acceptance criteria
• Data migration and integration requirements
• Data-quality measures and performance indicators
• Implementation risk and dependency assessment
• Change-management, training, and adoption recommendations
• Knowledge-transfer materials and operating documentation

Measures of Success

• A clearly defined and stakeholder-approved PIM strategy and roadmap
• Improved completeness, accuracy, consistency, and governance of product information
• Reduced manual effort and duplication across product-data processes
• Faster product onboarding, enrichment, approval, and publishing
• Stronger coordination among business, technology, and digital-commerce teams
• Prioritized AI use cases supported by clear business value and appropriate controls
• Successful implementation and adoption of a scalable PIM capability
• Effective transfer of knowledge and ownership to internal teams

Engagement Details

• Engagement type: Consulting engagement
• Location: Remote, Canada
• Engagement duration: 12 months
• Expected start date: October 2026
• Language requirements: English
• Security or background-screening requirements: Enhanced

Call to Action

If you are a qualified candidate looking to make a significant impact in a dynamic environment, we encourage you to apply for the PIM AI Product Manager position. Click the apply button to submit your application or for more information. We look forward to hearing from you!