Senior Cloud Engineer – AI

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BMO U.S.

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

🛡️ Insurance

💼 Consulting

📦 Logistics

Insurance • Consulting • Logistics

BMO U. S. is a diversified financial services company operating in the United States. It offers a broad range of financial products and services including personal and business banking, mortgage services, investments, financial planning, insurance, and wealth management. Additionally, it provides commercial loans, commercial mortgages, and other financial solutions tailored for small businesses and large enterprises. The company places a strong emphasis on customer service and offers digital and cross-border banking solutions to meet the needs of diverse clients. BMO U. S. is also involved in asset management and capital markets operations, making it a full-service financial institution.

📋 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 • 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 • 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, or 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 • 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 preferred • Experience with vector databases and embedding models • Knowledge of model optimization and inference acceleration • Background in financial services or banking

🏖️ Benefits

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