Chief AI Architect, Scotiabank - Toronto, ON

AI Summary

Scotiabank in Toronto, Ontario, seeks a Chief AI Architect. This senior role defines the enterprise AI solution architecture and leads the Enterprise AI and Agentic Solution Architecture group. Key duties involve translating AI strategy into architectural decisions across business lines and platforms. Candidates need over 12 years of technology and architecture experience, with deep mastery of enterprise AI solution architecture.

About the Role and Strategic Impact

The Chief AI Architect serves as the definitive technical voice for enterprise AI solution design across Scotiabank, operating as the most senior architecture authority in AI and Agentic Engineering. This pivotal role leads the Enterprise AI and Agentic Solution Architecture group, a function crucial for translating Scotiabank's overarching enterprise AI strategy into coherent, governed, and production-viable solution architectures. These architectural designs are expected to span various business lines, diverse platforms, and multiple geographies. While this architect does not directly build the AI platform or own feature delivery, they are instrumental in defining how AI capabilities are strategically assembled into complete business solutions. Furthermore, this role establishes the architectural standards that will govern all AI solution builds across the bank, ensuring that significant platform investments in AI and machine learning infrastructure are precisely mapped to desired enterprise business outcomes with robust architectural precision. This position is a technical peer to the Head of AI and Agentic Engineering, becoming the trusted expert for critical enterprise AI architecture decisions with lasting consequences for the institution.

Key Responsibilities and Leadership

A core responsibility involves defining Scotiabank's enterprise AI solution architecture, which includes creating canonical reference architectures, solution patterns, and integration blueprints. These foundational documents will govern how GenAI, agentic AI, and ML capabilities are assembled and deployed across all business lines, customer-facing products, and internal operations at scale. The Chief AI Architect will also lead the Enterprise AI and Agentic Solution Architecture group, setting the architectural direction for the team and actively building architectural capacity by developing architects from Senior to Principal levels. This includes establishing a clear design authority review cadence and criteria, ensuring the group functions as an accelerator for AI solution delivery rather than a governance bottleneck. A critical aspect of the role is translating Scotiabank's enterprise AI strategy and specific business line requirements into actionable architecture-level decisions. This encompasses platform capability mapping, integration architecture, data architecture dependencies, deployment topology, and crafting end-to-end solution blueprints that engineering teams can implement without ambiguity.

Required Expertise and Influential Leadership

To succeed in this challenging architecture role, candidates must possess over 12 years of extensive technology and architectural experience, with a minimum of five years serving as the architecture authority of record for AI, data, or platform initiatives within a Tier 1 financial institution or an enterprise of comparable scale and regulatory complexity. Deep mastery of enterprise AI solution architecture is paramount, enabling the design of complete, end-to-end AI solutions. This expertise should span LLM integration, AI architecture, Machine Learning Architecture, MLOps Architecture, Cloud Architecture, agentic harnesses, agentic workflow composition, data platform dependencies, API integration topology, and production observability. Proficiency in enterprise integration architecture as applied to AI is also essential, covering event-driven integration patterns for AI-augmented banking workflows, API management strategy for AI capability exposure, and the specific requirements for embedding AI into core banking systems with the necessary latency, reliability, idempotence, and audit trail guarantees for regulated financial operations. The role demands a proven ability to translate regulatory requirements, such as OSFI E-23 model risk management and enterprise AI governance policy, into embedded architecture controls within solution designs from inception.