Principal Architect – AI Platform

This is a fully remote position, open to applicants in Texas.

📋 Description

• Take ownership of architectural consistency for AI across BMO's cloud and workspace environments, including AWS, Azure, Microsoft 365, and SaaS AI interfaces.

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

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

• Prepare architecture decisions for cross-organizational approval by the Council and resolve Microsoft AI boundary inquiries.

• Assess preview AI features against bank governance standards and escalate unresolved issues to Engineering leadership and Enterprise Architecture.

• Define and sustain the enterprise target AI architecture, reference architectures, standards, and guidelines.

• Establish architectural direction across Directors, squads, Security, DevOps, and Data Engineering.

• Review major AI initiative designs for coherence, scalability, security, cost effectiveness, residency, Responsible AI, and compliance with regulations.

• Represent significant AI initiatives at the Architecture Review Board.

• Ensure architectural coherence of BMO's Microsoft AI interface, which includes Copilot, Copilot Studio, Fabric Copilot, and Microsoft Agent 365.

• Lead the evaluation of new AI capabilities, foundational models, and architectural strategies.

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

• Ensure domain patterns are in alignment with the target architecture.

• Mentor architects and principal engineers throughout the function.

• Develop and manage transition architecture for AI-incubated platforms that are eligible for bank-wide ownership as they progress toward enterprise status.

⛳️ Requirements

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

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

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

• More than 3 years concentrating on AI/ML and GenAI architecture.

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

• Experience in holding architectural authority across teams or organizations.

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

• Working knowledge of model-risk management and regulatory standards such as OSFI and OCC.

• 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, Cedar, OPA, workload identity, zero-trust, SPIFFE/SPIRE, federated identity, guardrails, and AI observability.

• Proficiency in multi-cloud architecture across AWS and Azure.

• Experience with Microsoft AI products, including M365 Copilot, Copilot Studio, Fabric, and Agent 365.

• Knowledge of cloud security and IAM applied to AI workloads.

• Experience with integration architecture utilizing APIs, event-driven patterns, and data services.

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

• Adequate hands-on ability to prototype and assess approaches; Python is preferred.

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

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

• Excellent interpersonal, communication, and facilitation abilities.

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

• Self-motivated and capable of operating within a broad mandate and ambiguity.

• Ability to function under tight deadlines on complex, high-stakes decisions.

• AWS Certified Solutions Architect – Professional or AWS Certified Machine Learning – Specialty is highly preferred.

• Microsoft Certified: Azure Solutions Architect Expert or Azure AI Engineer Associate is highly preferred.

• Google Cloud Professional Machine Learning Engineer is highly preferred.

• TOGAF or equivalent enterprise architecture certification is highly preferred.

• Relevant GenAI/LLM credentials are highly preferred.

🏝️ Benefits

• Performance-based incentives.

• Discretionary bonuses.

• Health insurance.

• Tuition reimbursement.

• Accident and life insurance.

• Retirement savings plans.

• Comprehensive training and coaching.

• Support from management.

• Networking opportunities.

• Access to tools and resources for achieving new milestones.

• Reasonable accommodations for individuals with disabilities.