Director, AI Architecture B2C

Director AI Architecture

BMO is investing heavily in AI-powered customer experiences, personalization, digital banking, employee copilots, and intelligent decisioning. The B2C space allows you to influence how customers discover products, receive advice, interact with digital channels, and manage their finances. As an AI Architecture leader, your work isn't an experimental lab project. It directly affects customer acquisition, engagement, servicing, and retention. Unlike many organizations that are still piloting AI, BMO has established enterprise-wide AI capabilities and recently created the BMO Institute for Applied Artificial Intelligence & Quantum to accelerate innovation while maintaining governance.

This role offers the chance to:

• Define AI reference architectures
• Build reusable AI platforms
• Drive GenAI adoption across business units
• Influence long-term technology strategy

AI has become a board-level and CEO-level priority across banking. BMO has publicly highlighted AI as a strategic differentiator and has invested significantly in AI talent and innovation.

A Director AI Architecture role provides visibility with:

• Technology executives
• Business executives
• Risk and compliance leaders
• Enterprise architecture leadership

KEY

Job Responsibilities:

• Designs and architects AI IT Systems that integrate business processes, customer experiences, applications, data, machine learning models, generative AI capabilities, and technology platforms, ensuring alignment with business objectives, responsible AI principles, regulatory requirements, and enterprise technology standards.
• Leads the planning, evaluation, and optimization of AI-enabled capabilities, including Generative AI, Agentic AI, and intelligent automation.
• Ensures an integrated AI architecture across interdependent technology systems, data platforms, cloud and on-premises environments, and customer-facing digital channels.
• Creates and manages key AI architecture assets - blueprints, standards, reference architecture, governance frameworks etc. for the designated portfolio and business scope.
• Creates technical design recommendations aligned to standards for development and integration of AI (machine learning, generative AI, intelligent automation, AI platform capabilities (connectors/MCP etc.)) into new or existing products, services, and applications.
• Identifies risks or issues with AI solutions, model performance, ethical AI considerations, security vulnerabilities, compliance requirements, and solution design that may impact realization of project benefits; guides and supports stakeholders to make decisions that proactively resolve or mitigate potential project risks/delays.
• Stays abreast of industry technical and business trends through participation in professional associations, practice communities, and individual learning, with emphasis on AI, cloud technologies, analytics, and regulatory developments.
• Establishes and promotes Responsible AI practices including fairness, transparency, explainability, privacy, security, guardrails, observability, Evals, model governance, and regulatory compliance.
• Attracts, retains, and enables the career development of top talent in AI architecture.
• Improves team performance, recognizes and rewards performance, coaches employees, supports their development, and manages poor performance. Directs the delivery of AI architecture and transformation strategies across multiple business units.

KEY Skills and Experience :

Expertise with AI Security Skills :

• LLM security
• Prompt injection mitigation
• Data privacy
• Responsible AI controls
• RBAC implementation
• Compliance frameworks (SOC, HIPAA, GDPR)

Expertise with Cloud architecture:

• AWS AI Services:
• Amazon Sage Maker
• Amazon Bedrock Agent Core
• Amazon Lex
• Amazon Transcribe
• Amazon Translate
• Kendra Knowledge Search
• Azure AI Services:
• Azure AI Foundry
• Azure OpenAI Service
• Azure AI Search
• Azure AI Vision
• Azure AI Document Intelligence
• Azure AI Language
• Azure AI Speech
• Azure Machine Learning
• Azure Bot Service

Expertise with Security architecture :

• AWS:
• IAM
• KMS
• Secrets Manager
• Azure:
• Microsoft Entra
• Key Vault
• Microsoft Defender for Cloud
• Purview
• Azure Policy

Expertise with Technical architecture:

• LLM architecture and deployment
• Prompt engineering
• RAG (Retrieval-Augmented Generation)
• Vector databases
• AI orchestration frameworks
• Agentic AI design patterns
• Multi-agent architecture
• Fine-tuning and model customization
• Evals

Expertise with Infrastructure development

• AWS:
• Cloud Formation
• AWS CDK
• Terraform
• Azure:
• ARM Templates
• Bicep
• Terraform

Experience with managing teams/people.

Additional Information related to the duties and skills of the role:

• Performs planning, problem-solving, and advising technical teams to optimize AI-enabled solutions that are strategic, operational, secure and economical
• Participates in the system specification review process to ensure system requirements can be translated into valid AI, data, and software architecture designs that are scalable, explainable, secure, and operationally sustainable.
• Identifies and researches relevant technologies,…