Azure Google AI/ML Platform Engineer II

TD•Toronto, ON

2d•Onsite

About The Position

Our mission is to advance TD by enabling secure, scalable Azure and Google Cloud AI/ML capabilities across the enterprise to solve business problems with AI and deliver solutions to customers faster. We are a multi-cloud Platform Engineering team, building Infrastructure as Code (IaC), automated testing frameworks, and self-service tooling that allow lines of business to consume cloud services safely within a financial services environment. As an experienced Platform Engineer, you own services end-to-end. You design the Terraform modules, the GitHub Actions pipelines, the security model, and the operational story for an entire cloud service. You provide technical oversight to other engineers for code review, design feedback, and mentorship. You raise the bar on quality, security, and developer experience for the entire platform. You will work across a modern, opinionated platform stack: Terraform and the native Azure/Google SDKs for IaC; Python for automation and tooling; GitHub Actions for CI/CD; and a security-first toolchain spanning RBAC/IAM, Active Directory, PingFederate, PKI, Key Vault / Secret Manager, and policy-as-code. The services in scope include Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Bot Service, Azure ML, and Google Vertex AI.

Requirements

5+ years of cloud platform or infrastructure engineering experience, with deep IaC delivery on at least one of Azure or Google Cloud.
Expert-level Terraform - module design, composition, workspaces, testing, drift management, and pipeline patterns.
Strong Python for platform work: SDK integrations, CLI/tooling, automated testing, packaging, observability hooks.
Experience with GitHub Actions (or comparable CI/CD) including reusable workflows, environments, OIDC-based cloud auth, deployment gating, and secret management.
Demonstrable experience deploying and operating AI/ML services on Azure (Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Bot Service, Azure ML) and/or Google Cloud (Vertex AI, BigQuery, Pub/Sub).
Hands-on understanding of cloud networking at depth: VNets/VPCs, NSGs/firewall rules, hub-spoke and shared VPC patterns, private endpoints, ExpressRoute, DNS, and routing across hybrid topologies.
Strong security engineering instincts: RBAC/IAM design, identity federation (Azure AD/Entra, Google Cloud Identity, AD, PingFederate), Key Vault / Secret Manager, PKI and certificate lifecycle, data protection, and policy-as-code.

Responsibilities

Own end-to-end delivery of Infrastructure as Code for one or more cloud AI services - Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Bot Service, Azure ML, or Google Vertex AI - from Terraform module design and pipeline plumbing through to production rollout and Day-2 operations.
Design platform abstractions that let application teams self-serve safely: opinionated Terraform modules, GitHub Actions reusable workflows, Python CLIs and SDKs, and golden paths that bake in security, networking, and observability.
Lead architectural conversations across Azure and Google Cloud, balancing capability, cost, performance, regulatory fit, and developer experience.
Embed security and compliance into the platform: RBAC/IAM design, federated identity (Azure AD/Entra, Google Cloud Identity, AD, PingFederate), private networking, certificate/PKI lifecycle, secrets management, policy-as-code, and audit/evidence workflows.
Build patterns for safe consumption of generative AI - private endpoints for Azure OpenAI and Vertex AI, RAG architectures with Azure AI Search and vector stores, model gateway / routing layers, content filtering and prompt-shield controls, MLOps/LLMOps pipelines, and evaluation tooling.
Lead code review and set standards for IaC quality, testing, observability, error handling, and runbook hygiene across the team.
Partner with security, network, risk, and architecture organizations to shepherd new capabilities through internal control gates.
Contribute to platform strategy: roadmap shaping, build-vs-buy analysis, vendor evaluations, and cross-team alignment.