Senior Product Manager, Enterprise AI

Title: Senior Product Manager, Enterprise AI

Location

Toronto, ON

Duration: 6 months contract

Work Model: Hybrid ( 3 days per week onsite)

Pay rate

100$/hour on Incorp

Introduction

The role will design and evolve enterprise data architecture and data models to enable scalable analytics, AI, and data products. The position will help establish the future-state data architecture, identify critical data assets, and define standards and integration patterns that enable data to be governed, reusable, accessible, and AI-ready.

Required Skills & Qualifications

• Degree in Computer Science, Information Systems, Data Management, Engineering, or a related discipline, or equivalent experience.
• Significant experience in enterprise data architecture, data modelling, data engineering, or related disciplines.
• Demonstrated experience developing conceptual, logical, and physical data models and enterprise data architectures.
• Experience designing modern data architectures supporting cloud, analytics, AI/ML, and enterprise integration.
• Strong knowledge of data modelling, data integration, APIs, data platforms, metadata, master/reference data, and data quality concepts.
• Prior work experience at client or in client's Industry.

Must Haves

Strong experience delivering AI/ML, Generative AI, and data products, with sufficient technical depth to challenge solution approaches, assess architecture and model choices, and guide technical teams.

Strong working knowledge of Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, LLMs, RAG, machine learning, analytics, and enterprise data platforms, including an understanding of AI/ML pipelines, model evaluation, predictive modelling, and related techniques.

Significant experience in technical product management or product ownership, including developing product strategies, technical roadmaps, prioritization frameworks, and business cases, and translating complex business requirements into scalable AI solutions that deliver measurable value.

Preferred Skills & Qualifications

• Understanding of data governance, data ownership, lineage, security, privacy, and information lifecycle management.
• Knowledge of modern architecture approaches such as data lakehouse, data products, domain-oriented architecture, and cloud-based data platforms.
• Ability to translate complex business and technical requirements into practical architecture standards, models, and patterns.

Day-to-Day Responsibilities

• Design and maintain enterprise data architecture and conceptual, logical, and physical data models supporting AI, analytics, and operational use cases.
• Define scalable architecture patterns for the integration, storage, transformation, sharing, and consumption of enterprise data.
• Design reusable data products and common data models that can support multiple business and AI use cases.
• Contribute to the organization's future-state data architecture, including transition from existing platforms and architectures.
• Identify and define critical data assets and domains required to support enterprise priorities.
• Establish and promote enterprise data architecture, modelling, interoperability, and integration standards.
• Partner with Data Governance teams to embed data ownership, quality, metadata, lineage, classification, and lifecycle requirements into architecture and data products.
• Assess data requirements and architecture implications for AI, Generative AI, machine learning, advanced analytics, and reporting initiatives.
• Work with business, Data & AI, architecture, engineering, and technology teams to translate business requirements into scalable data solutions.
• Identify architecture gaps, duplication, data silos, and opportunities to improve data reuse and interoperability across the enterprise.

For immediate consideration please click APPLY to begin the screening process with Alex.