Azure Google AI​/ML Associate Platform Engineer

Position: Azure Google AI/ML Associate Platform Engineer I
## Ingénieur ou ingénieure IPostulerremote type:
Hybridelocations:
Toronto, Ontario time type:
Temps pleinposted on:
Publié aujourd'huitime left to apply:
Date de fin : 25 mai 2026 (Il reste 3 jours pour postuler) job requisition : R  
** Lieu de travail :
** Toronto, Ontario, Canada
** Horaire :
** 37.5
** Secteur d’activité :
** Solutions technologiques
** Détails de la rémunération :**$81,600 - $115,200 CADLa TD a à cœur d’offrir une rémunération juste et équitable à tous les collègues. Les occasions de croissance et le perfectionnement des compétences sont des caractéristiques essentielles de l’expérience collègue à la TD. Nos politiques et pratiques en matière de rémunération ont été conçues pour permettre aux collègues de progresser dans l’échelle salariale au fil du temps, à mesure qu’ils s’améliorent dans leurs fonctions.

Le salaire de base offert peut varier en fonction des compétences et de l’expérience du candidat, de ses connaissances professionnelles, de son emplacement géographique et d’autres besoins particuliers du secteur et de l’entreprise. En tant que candidat, nous vous encourageons à poser des questions sur la rémunération et à avoir une conversation franche avec votre recruteur, qui pourra vous fournir des détails plus précis sur ce poste.
** Description du poste :
** 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 associate Platform Engineer, you will learn and help Senior platform engineers design the Terraform modules, the Git Hub Actions pipelines, the security model, and the operational story for an entire cloud service. You will help with design, developing and testing.

You will work across a modern, opinionated platform stack:
Terraform and the native Azure/Google SDKs for IaC;
Python for automation and tooling;
Git Hub Actions for CI/CD; and a security-first toolchain spanning RBAC/IAM, Active Directory, Ping Federate, 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.
** KEY

ACCOUNTABILITIES
*** Help with 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, Git Hub Actions reusable workflows, Python CLIs and SDKs, and golden paths that bake in security, networking, and observability.
* Embed security and compliance into the platform: RBAC/IAM design, federated identity (Azure AD/Entra, Google Cloud Identity, AD, Ping Federate), 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.
** EXPERIENCE & EDUCATION
*** 1+ years of cloud platform or infrastructure engineering experience, with IaC delivery on at least one of Azure or Google Cloud.
* Terraform - module design, composition, work spaces, testing, drift management, and pipeline patterns.
* Python for platform work: SDK integrations, CLI/tooling, automated testing, packaging, observability hooks.
* Experience with Git Hub 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…