Senior Cloud Engineer, AI

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BMO

WebsiteLinkedInAll Job Openings

10,000+ employees

🏦 Banking

💸 Finance

🔥 Funding within the last year

💰 $142.9M Post IPO debt on 2025-11

Banking • Finance

BMO is the Bank of Montreal, a major Canadian financial institution that provides retail and commercial banking services in Canada and the United States. The provided site text highlights separate Canadian and U. S. banking experiences and bilingual (English/French) support, indicating a consumer-facing bank serving individuals and businesses across North America.

📋 Description

• Evaluate and enable AWS and Azure AI/ML services through proof-of-concepts and comprehensive assessments • Design and implement reusable architectural patterns for secure AI/ML integrations, including private endpoints, customer-managed keys, and service-to-service authentication • Build end-to-end MLOps platforms and automated ML pipelines for model training, evaluation, deployment, and monitoring • Produce technical reports on security, networking, compliance, guardrails, and cost analysis for AI/ML service enablement • Develop frameworks, infrastructure-as-code, and automation to accelerate AI/ML adoption • Implement observability solutions with model monitoring, metrics, and drift detection • Partner with Enterprise Architecture and senior stakeholders to align platform capabilities with strategic roadmaps • Provide technical leadership and mentorship on AI/ML cloud best practices

🎯 Requirements

• 5–7 years of cloud engineering experience, with 3+ years focused on AI/ML platforms • Deep hands-on expertise with AWS AI/ML services, including SageMaker and Bedrock • Deep hands-on expertise with Azure AI/ML services, including Azure Machine Learning, Azure OpenAI, and Azure AI Foundry • Experience building MLOps platforms and automated ML pipelines • Strong knowledge of LLMOps, LLM lifecycle management, agentic AI, RAG, and prompt engineering • Experience implementing guardrails and governance for LLM services • Proficiency in Python and infrastructure-as-code using Terraform, CloudFormation, and ARM/Bicep • Experience with MLflow or similar tools, experiment tracking, and model registries • Expertise in cloud security patterns, including private endpoints, customer-managed keys, and network isolation for AI/ML services • Strong understanding of cloud networking architecture in regulated environments • Experience working in highly regulated industries with compliance requirements • Agile delivery experience • AWS or Azure AI/ML certifications are nice to have • Experience with vector databases and embedding models is nice to have • Knowledge of model optimization and inference acceleration is nice to have • Background in financial services or banking is nice to have

🏖️ Benefits

• Performance-based incentives • Discretionary bonuses • Health insurance • Tuition reimbursement • Accident and life insurance • Retirement savings plans • In-depth training and coaching • Manager support • Network-building opportunities • Tools and resources to reach new milestones • Equal employment opportunity • Reasonable accommodations for individuals with disabilities