Principal Architect AI Platform

Description

BMO is establishing a dedicated AI Engineering function, and this role is its singular architectural authority. We are seeking a deeply experienced architect to own architectural coherence for AI across BMO's cloud and workspace estates — spanning AWS, Azure, Microsoft 365, and SaaS AI surfaces, and two regulatory regimes (OSFI, OCC).

You will hold architectural oversight across the AI Platform capabilities including Developer Experience, Security, DevOps, and Data Analytics. You will work across teams and organizations to bring a cohesive and integrated AI Platform build and operations. You will set the architectural direction that keeps teams working on Enterprise AI initiatives aligned, prevent the fragmentation and rework, and serve as the standing architectural authority to the Microsoft AI Council, preparing decisions for ratification and escalating unresolved matters to Engineering leadership and Enterprise Architecture.

You bring the technical depth to earn credibility with principal engineers, the judgment to make defensible architectural decisions under ambiguity, and the influence to align senior leaders on architectural directions.

The Mandate

• Singular architectural oversight across the AI Engineering function and across Cloud AI and Workspace Engineering for all AI surfaces.

• Standing architectural authority to the Microsoft AI Council: prepare cross-organizational architecture decisions for Council ratification, adjudicate Microsoft AI boundary questions, and evaluate preview features against bank governance. Enterprise Architecture serves as formal arbiter for unresolved disputes.

• Architectural coherence across planes and platforms: ensure the Control Plane, Domain Orchestration, and domain-owned execution fit together into one coherent, governed architecture.

• Regulatory-defensible architecture: ensure architectural decisions produce model-risk and regulatory evidence (OSFI E-23, OCC) at runtime, by design.

What You'll Do

• Define and maintain the target AI architecture for the enterprise: reference architectures, architectural standards, and the guardrails that governed platform capabilities and domain workloads must conform to.

• Set architectural direction across the function's Directors and squads (Platform & Fabrics, Developer Experience) and across sibling disciplines (Security, DevOps, Data Engineering), resolving competing approaches into a coherent whole.

• Provide architectural governance for major AI initiatives: reviewing designs for coherence, scalability, security, cost, residency, Responsible AI, and regulatory fit and represent them at Architecture Review Board.

• Own the architectural coherence of BMO's Microsoft AI surface (Copilot, Copilot Studio, Fabric Copilot, Microsoft Agent 365) across the two operating organizations, including the Three-Zone citizen governance framework and federation with the AI Registry.

• Lead assessment of emerging AI capabilities, foundation models, and architectural approaches; translating rapid market change into deliberate, defensible architectural positions for the bank.

• Partner with AI Platform & Fabrics to ensure platform capabilities (Gateway, Policy Engine, Identity Fabric, Registry, Guardrails, Observability) realize the target architecture, and with AI Developer Experience / Domain Solution Architects to ensure domain patterns conform to it.

• Provide architectural mentorship and technical leadership to architects and principal engineers across the function, growing architectural capability and consistency.

• Establish and steward the transition architecture for AI-incubated, bank-wide-eligible platforms (Identity Fabric, Policy Engine) as they mature toward enterprise ownership.

Education & Experience

• Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline (Master's preferred).

• 10+ years in software engineering, solution architecture, and enterprise architecture, with substantial time at a principal/senior architect level setting direction across multiple teams.

• 3+ years focused on AI/ML and GenAI architecture, including hands-on exposure to production GenAI systems (RAG, agentic workflows, model serving, guardrails).

• Demonstrated experience holding cross-team or cross-organizational architectural authority — setting standards others must follow, and aligning senior stakeholders without direct reporting lines.

• Experience architecting AI in a regulated industry (financial services strongly preferred), with a working understanding of model-risk management and regulatory expectations (OSFI, OCC, or equivalent).

Required Core Skills

Architectural Authority & Leadership

• Proven ability to establish architectural coherence across multiple teams and organizations: defining target-state architecture, standards, and governance that hold under contested decisions.

• Executive presence and influence: the credibility to advise Directors and senior executives, the judgment to make defensible decisions under ambiguity, and the diplomacy to align organizations with different mandates.

• Strong mentoring and technical leadership across architects and principal engineers; ability to raise the architectural bar across a function.

• Skilled at chairing/supporting governance forums, preparing decisions for ratification, and managing structured escalation.

AI & Platform Architecture Depth

• Deep AI/ML and GenAI solution architecture: RAG, agentic frameworks, prompt patterns, fine-tuning, foundation models, embeddings, and vector stores.

• Strong grasp of AI platform architecture: AI gateways, policy-as-code/authorization (Cedar, OPA), workload identity and zero-trust (SPIFFE/SPIRE, federated identity), guardrails, and AI observability.

• Multi-cloud architecture across AWS and Azure, plus Microsoft AI surfaces (M365 Copilot, Copilot Studio, Fabric, Agent 365); cloud security and IAM as applied to AI workloads.

• Integration architecture connecting AI to enterprise systems via APIs, event-driven patterns, and data services.

• Working knowledge of MLOps/LLMOps, CI/CD, and how architectural decisions translate into deployable, operable patterns.

• Sufficient hands-on fluency (Python preferred) to prototype, evaluate approaches, and earn engineering credibility.

Governance & Responsible AI

• Deep grounding in Responsible AI, AI/data governance, privacy, and evaluation/guardrail design.

• Experience embedding regulatory and model-risk evidence requirements into architecture, produced at runtime rather than retroactively.

Certifications (Preferred)

One or more strongly preferred:

• AWS Certified Solutions Architect – Professional; AWS Certified Machine Learning – Specialty

• Microsoft Certified: Azure Solutions Architect Expert; Azure AI Engineer Associate

• Google Cloud Professional Machine Learning Engineer

• TOGAF or equivalent enterprise architecture certification

• Relevant GenAI/LLM credentials

Other Skills

• Strong interpersonal, communication, and facilitation skills across technical and business audiences.

• A critical thinker with strong research, analytical, and problem-solving skills.

• Self-directed, comfortable operating with broad mandate and ambiguity.

• Able to work under tight timelines on complex, high-stakes decisions.