Principal Architect – AI Platform

This is a fully remote position, open to applicants in California, +4 more states.

📋 Description

• Take charge of architectural consistency for AI within BMO's cloud and workspace environments, covering AWS, Azure, Microsoft 365, and SaaS AI platforms.

• Provide comprehensive architectural oversight for the AI Engineering function along with Cloud AI and Workspace Engineering.

• Act as the primary architectural authority for the Microsoft AI Council.

• Prepare architectural decisions for cross-organizational collaboration, seeking Council ratification and escalating unresolved issues to Engineering leadership and Enterprise Architecture.

• Define and uphold the target enterprise AI architecture, including reference architectures, standards, and platform guidelines.

• Direct architectural strategies across Directors, squads, Security, DevOps, and Data Engineering teams.

• Integrate competing methodologies into a unified architectural framework.

• Review significant AI initiative designs for coherence, scalability, security, cost, residency, Responsible AI, and regulatory compliance.

• Represent key AI initiatives at the Architecture Review Board.

• Ensure architectural consistency for BMO's Microsoft AI offerings, such as Copilot, Copilot Studio, Fabric Copilot, Microsoft Agent 365, the Three-Zone citizen governance framework, and AI Registry federation.

• Lead the evaluation of emerging AI capabilities, foundational models, and architectural methodologies.

• Collaborate with AI Platform & Fabrics to align Gateway, Policy Engine, Identity Fabric, Registry, Guardrails, and Observability with the target architecture.

• Work with AI Developer Experience and Domain Solution Architects to ensure domain patterns align with the target architecture.

• Mentor architects and principal engineers to enhance architectural skill and consistency.

• Establish and manage transition architecture for AI-incubated platforms eligible for bank-wide use as they evolve toward enterprise ownership.

⛳️ Requirements

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

• Over 10 years of experience in software engineering, solution architecture, and enterprise architecture.

• Significant experience at a principal or senior architect level, guiding direction across multiple teams.

• At least 3 years of specialization in AI/ML and GenAI architecture.

• Practical experience with production GenAI systems, including RAG, agentic workflows, model serving, and guardrails.

• Proven experience in holding architectural authority across teams or organizations.

• Background in architecting AI solutions within regulated industries; experience in financial services is highly preferred.

• Familiarity with model-risk management and regulatory expectations, such as OSFI, OCC, or equivalent.

• Extensive knowledge of AI/ML and GenAI solution architecture, including RAG, agentic frameworks, prompt patterns, fine-tuning, foundational models, embeddings, and vector stores.

• Strong understanding of AI platform architecture, including AI gateways, policy-as-code/authorization, workload identity, zero-trust, guardrails, and AI observability.

• Experience with multi-cloud architectures, particularly AWS and Azure.

• Familiarity with Microsoft AI offerings, including M365 Copilot, Copilot Studio, Fabric, and Agent 365.

• Knowledge of cloud security and IAM principles as they pertain to AI workloads.

• Competence in integration architecture utilizing APIs, event-driven patterns, and data services.

• Working knowledge of MLOps/LLMOps and CI/CD practices.

• Adequate hands-on proficiency, preferably in Python, to prototype and assess methodologies.

• Strong foundation in Responsible AI, AI/data governance, privacy, and evaluation/guardrail design.

• Experience in incorporating regulatory and model-risk evidence requirements into architectural designs.

• Excellent interpersonal, communication, and facilitation abilities.

• Strong critical thinking, research, analytical, and problem-solving capabilities.

• Self-motivated and comfortable operating within a broad mandate and uncertain situations.

• Capable of working under tight deadlines on complex, high-stakes decisions.

🏝️ Benefits

• Performance-based incentives.

• Discretionary bonuses.

• Health insurance coverage.

• Tuition reimbursement programs.

• Accident insurance policies.

• Life insurance options.

• Retirement savings plans.

• Comprehensive training and coaching opportunities.

• Support from management.

• Opportunities for networking and relationship-building.

• Access to tools and resources to achieve new milestones.