Principal AI Cloud Engineer

Application Deadline: 11/30/2026 Address: 100 King Street West Job Family Group: Data Analytics & Reporting 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. 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 Impact

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-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 You

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. Partner with a leadership team invested in your growth and thought leadership. Responsibilities

Infrastructure & Platform Builder

Design, build, and operate cloud-native AI infrastructure for ML/GenAI workloads: Compute: GPU/CPU clusters, autoscaling, spot instance strategies 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: Metrics (latency, throughput, GPU utilization, cost) Logging/tracing (OpenTelemetry), SLOs/SLIs for infra services 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 Application & Service Enablement

Enable frontend and backend services for AI platforms: Secure APIs, microservices, and event-driven architectures Integration with custom model runtimes (TensorRT-LLM, vLLM, Triton/KServe) Provide infrastructure support for RAG systems: embeddings, chunking, retrieval pipelines Ensure scalable serving infrastructure for LLMs and ML models with caching and token optimization Strategy & Architecture

Define and evolve AI infrastructure reference architecture for cloud (Azure preferred): Container orchestration (Kubernetes), service mesh, ingress Serverless/event-driven patterns for AI pipelines Multi-region, HA/DR, compliance-ready designs 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 Delivery & Operations

Lead infrastructure discovery and solution design with stakeholders Operate platforms with SRE principles: error budgets, incident response, chaos testing Mentor engineers; create reusable IaC modules, templates, and golden paths Must-Have Qualifications

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 Strong in IaC (