Azure Google AI/ML Platform Engineer II
$96.9k - $136.8k per yearUnited States Digital Space LLC
Location: Toronto, Ontario, Canada
Hours: 37.5 hours per week
Line of Business: Technology Solutions
Pay: $96,900 - $136,800 CAD (subject to annual reassessment)
Job Overview
Our mission is to advance TD by enabling secure, scalable Azure and Google Cloud AI/ML capabilities across the enterprise. As part of a multi‑cloud Platform Engineering team, you will build 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 will own services end‑to‑end, including Terraform module design, GitHub Actions pipelines, security model, and operational story for an entire cloud service. You will provide technical oversight to other engineers, set standards for quality, security, and developer experience, and raise the bar across the platform.
Key Accountabilities
- Own end‑to‑end delivery of IaC 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 module design and pipeline plumbing through 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.
Experience & Education
- 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.
Benefits
Competitive base salary, variable compensation, health and well‑being benefits, savings and retirement plans, paid time off, career development, and recognition programs.
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