Principal Cloud Engineer AI

Application Deadline:11/30/2026Address:320 S Canal StreetJob Family Group:Data Analytics & ReportingThe 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. Above all, we are a global team of diverse individuals who enjoy working together to create smart, secure, and scalable solutions that make an impact across the enterprise. 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.
The ImpactAs 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-efficient 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; multi-cloud aware).
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.
What’s In It for YouInfluence 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.
Partner with a leadership team invested in your growth and thought leadership.
Responsibilities Infrastructure & Platform BuilderDesign, build, and operate cloud-native AI infrastructure for ML/GenAI workloads:Compute: GPU/CPU clusters, autoscaling, spot instance strategiesNetworking: Azure VNet, Private Link, peering, multi-region HA/DRStorage & 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-codeImplement observability and reliability for AI infra:Metrics (latency, throughput, GPU utilization, cost)Logging/tracing (OpenTelemetry), SLOs/SLIs for infra servicesBuild CI/CD and GitOps pipelines for infrastructure-as-code (Terraform/Bicep) and AI platform componentsDrive FinOps for AI infra: GPU rightsizing, caching, inference optimization, cost governanceApplication & Service EnablementEnable frontend and backend services for AI platforms:Secure APIs, microservices, and event-driven architecturesIntegration with custom model runtimes (TensorRT-LLM, vLLM, Triton/KServe)Provide infrastructure support for RAG systems: embeddings, chunking, retrieval pipelinesEnsure scalable serving infrastructure for LLMs and ML models with caching and token optimizationStrategy & ArchitectureDefine and evolve AI infrastructure reference architecture for cloud (Azure preferred):Container orchestration (Kubernetes), service mesh, ingressServerless/event-driven patterns for AI pipelinesMulti-region, HA/DR, compliance-ready designsEstablish standards and best practices for containerization, IaC, and secure networking for AI systemsSecurity, Risk & GovernanceImplement defense-in-depth for AI infra:IAM least privilege, private networking, KMS/Key Vault, SBOM, image signingEnsure compliance and Responsible AI controls at infra level:Data residency, encryption, lineage, audit readinessDelivery & OperationsLead infrastructure discovery and solution design with stakeholdersOperate platforms with SRE principles: error budgets, incident response, chaos testingMentor engineers; create reusable IaC modules, templates, and golden pathsMust-Have QualificationsBachelor’s/Master’s/PhD in CS, Engineering, or related field7+ years building large-scale distributed cloud infrastructure5+ years hands-on with Azure/AWSProven experience with AI/ML infra: GPU clusters, Kubernetes, CI/CD, observabilityStrong in IaC (Terraform/Bicep), Kubernetes, networking, securityExpertise in cloud-native patterns: containers, service mesh, serverlessFamiliarity with MLOps/LLMOps infra: model serving, feature stores, vector DBsProgramming in Python (infra automation) and one of Go/TypeScript for toolingUnderstanding of fronten