Senior Cloud Engineer ML/AI Platform

Job Description

Application Deadline: 06/29/2026 Address: 250 Yonge Street Job Family Group: Technology Senior Cloud Engineer – ML/AI Platform We are seeking a Senior Cloud Engineer with deep expertise in AWS and Azure AI/ML services to drive our enterprise ML/AI platform capabilities. You will evaluate and enable cloud AI/ML services, build reusable architectural patterns, and develop automated MLOps solutions in a highly regulated banking environment. This role requires hands-on experience with modern AI/ML platforms and the ability to design secure, compliant solutions that accelerate AI adoption across the organization. What You Will Do • Evaluate and enable AWS and Azure AI/ML services (SageMaker, Bedrock, Azure OpenAI, Azure AI Foundry) 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 What You Need to Succeed Must Have • 5-7 years of cloud engineering experience with 3 years focused on AI/ML platforms • Deep hands-on expertise with AWS AI/ML services: SageMaker (training, pipelines, inference, JumpStart), Bedrock • Deep hands-on expertise with Azure AI/ML services: Azure Machine Learning, Azure OpenAI, Azure AI Foundry • Experience building MLOps platforms and automated ML pipelines • Strong knowledge of LLMOps, LLM lifecycle management, agentic AI, RAG (retrieval-augmented generation), and prompt engineering • Experience implementing guardrails and governance for LLM services • Proficiency in Python and infrastructure-as-code (Terraform, CloudFormation, ARM/Bicep) • Experience with MLflow(or similar tool), 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 Nice to Have • AWS or Azure AI/ML certifications • Experience with vector databases and embedding models • Knowledge of model optimization and inference acceleration • Background in financial services or banking Salary : $75,900.00 - $141,900.00 Pay Type: Salaried The above represents BMO Financial Group’s pay r

Required Skills