Analyses des données et communication de l'information The Team - We accelerate BMO’s AI journey by building cloud-native AI solutions. Our team combines engineering excellence with cutting-edge AI to deliver scalable, secure, and responsible solutions that power business innovation across the bank. We enable and accelerate our partners on their AI journeys across the enterprise, helping teams across BMO unlock value at scale.

We support one another in times of need and take pride in our work. We are engineers, AI practitioners, platform builders, thought leaders, multipliers, and coders.

Our ambition is bold: deploy our capital and resources to their highest and most profitable use through a digital-first operating model, powered by data and AI-driven decisions. As a Principal AI & Cloud Engineer , you are a hands-on technical developer who designs, builds, and scales cloud-native AI solutions and products. You help set engineering standards, establish patterns, mentor senior engineers, and partner with multiple teams to deliver resilient, governed, and cost-effective AI at enterprise scale.

You’ll help shape and evolve our AI cloud strategy from model serving and LLMOps to security, observability, and compliance so teams across the bank can innovate safely and rapidly. You will advance BMO’s Digital First strategy by: Defining reference and production-grade solutions for AI/GenAI on cloud (Azure/AWS preferred; Building reusable, secure, and observable components (APIs, SDKs, microservices, pipelines). Operationalizing LLMs and RAG with strong controls and Responsible AI guardrails.

Driving platform roadmaps that enable faster delivery, lower risk, and measurable business outcomes. Influence the technical direction of AI and the platform primitives others build on. Ship high-impact systems used across many business lines and products.

Work across the full stack: cloud infra, data/feature pipelines, model serving,



LLMOps, and DevSecOps. Design, build, and operate cloud-native AI infrastructure for ML/GenAI workloads: Networking: Azure VNet, Private Link, peering, multi-region HA/DR Storage & Databases: high-performance data lakes (e.g., Azure Data Lake Storage), relational DBs, vector DBs (FAISS, Milvus, Pinecone, pgvector) Security: IAM, Key Vault-backed secrets management, encryption, policy-as-code Implement observability and reliability for AI infra: Build CI/CD and GitOps pipelines for infrastructure-as-code (Terraform/Bicep) and AI platform components Drive FinOps for AI infra: GPU rightsizing, caching, inference optimization, cost governance Enable frontend and backend services for AI platforms: Provide infrastructure support for RAG systems: embeddings, chunking, retrieval pipelines Ensure scalable serving infrastructure for LLMs and ML models with caching and token optimization Define and evolve AI infrastructure reference architecture for cloud (Azure preferred): Serverless/event-driven patterns for AI pipelines Establish standards and best practices for containerization, IaC, and secure networking for AI systems Security, Risk & Governance Implement defense-in-depth for AI infra: IAM least privilege, private networking, KMS/Key Vault, SBOM, image signing Ensure compliance and Responsible AI controls at infra level: Data residency, encryption, lineage, audit readiness Operate platforms with SRE principles: error budgets, incident response, chaos testing Bachelor’s/Master’s/PhD in CS, Engineering,



or related field ~7+ years building large-scale distributed cloud infrastructure ~5+ years hands-on with Azure/AWS ~ Proven experience with AI/ML infra: GPU clusters, Kubernetes, CI/CD, observability ~ Familiarity with MLOps/LLMOps infra: model serving, feature stores, vector DBs ~ Programming in Python (infra automation) and one of Go/TypeScript for tooling ~ Understanding of frontend/backend integration for AI services ~ Familiarity with MLOps/LLMOps infra: model serving, feature stores, vector DBs ~ Programming in Python (infra automation) and one of Go/TypeScript for tooling ~ Understanding of frontend/backend integration for AI services Experience with AI platform products (Azure ML, MLflow, KServe, Hugging Face) Reliability & Performance: SLOs met for infra services, GPU utilization optimized Developer Velocity: Faster provisioning and deployment of AI infra Technical Leadership: Influence on infra standards, mentorship, reusable patterns Les salaires pour les postes à temps partiel seront calculés au prorata du nombre d’heures travaillées régulièrement. BMO offre également une assurance santé, le remboursement des frais de scolarité, une assurance accident et une assurance vie, ainsi que des régimes d’épargne-retraite.

Pour en savoir plus sur nos avantages sociaux, consultez le site : Cette raison d’être nous invite à entraîner des changements positifs et durables pour nos clients, nos collectivités et nos gens. Nous vous offrirons les outils et les ressources dont vous avez besoin pour franchir de nouvelles étapes, car vous aidez nos clients à franchir les leurs. Au moyen de formation et de coaching approfondis ainsi que de soutien de la direction et d'occasions de réseautage, nous vous aiderons à acquérir une expérience enrichissante et à élargir votre groupe de compétences.

📌 Principal ai cloud engineer (Toronto)
🏢 BMO Financial Group
📍 Toronto