AI Architect/Designer

2 days ago

Toronto, Ontario, Canada Teckhorizon Inc Full time $120,000 - $180,000 per year

About The Role
Our Client is seeking a
Senior AI Architect/Designer
to lead the development of the division's short-term and long-term AI acceleration strategies. This role will define the roadmap for AI adoption, establish governance frameworks, and design scalable architectures aligned with organizational priorities. The consultant will collaborate with senior leadership to identify high-value use cases, build prioritization criteria, and ensure responsible AI practices across the division.

Key Responsibilities
AI Strategy and Governance

  • Develop and deliver a comprehensive AI acceleration strategy and roadmap.
  • Define KPIs and ROI models to measure business and technical impact.
  • Establish governance frameworks covering data strategy, compliance, and responsible AI principles.
  • Assess business value and technical feasibility of AI use cases for prioritization.
  • Identify organizational readiness needs and guide cultural/operational shifts for AI adoption.
  • Evaluate risks including bias, privacy, ethics, and regulatory non-compliance.
  • Advise on vendor selection, platform evaluation, and partnership opportunities.
  • Communicate complex AI concepts through executive-level briefings and documentation.

AI Implementation

  • Design scalable technical architectures for AI platforms, data pipelines, and integration patterns.
  • Recommend cloud-based AI solutions and guide the implementation of MLOps practices.
  • Work closely with business and technical stakeholders to ensure alignment and successful delivery.

Enterprise Architecture

  • Apply enterprise architecture frameworks (TOGAF, Zachman, or similar) to align AI initiatives with organizational standards.

Must-Have Experience

  • Proven experience developing and executing AI adoption strategies (short- and long-term).
  • Strong background in defining and implementing KPI and ROI frameworks.
  • Deep knowledge of AI governance: data strategy, compliance, responsible AI, and risk mitigation.
  • Expertise in evaluating business value and technical feasibility of AI use cases.
  • Hands-on experience designing scalable AI architectures, data pipelines, and integration patterns.
  • Experience with cloud-based AI solutions and MLOps lifecycle management.

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