Must be legally eligible to work in the United States without sponsorship, now or in the future, to be considered.

What you’ll do

We’re hiring an Azure Cloud Engineer to administer, operate, and govern cloud and AI solutions on Microsoft Azure. This is a hands-on engineering role for someone who can move fluidly between cloud architecture, infrastructure-as-code, CI/CD pipelines, and modern AI platform administration using Azure AI Foundry, Azure OpenAI, Anthropic’s Claude, and the Model Context Protocol (MCP).

You’ll oversee real workloads end-to-end: standing up Azure landing zones, automating deployments through pipelines, and administering, configuring, and operating AI platforms, models, and integrations that move the business forward. You’ll be a key contributor to how Customers Bank evolves into a more automated, AI-augmented, cloud-first organization.

Key Responsibilities

• Design and implement Azure solutions across compute, networking, identity, storage, and platform services, aligned to enterprise reference architectures and security standards.
• Build and maintain CI/CD pipelines in Azure DevOps and GitHub Actions for infrastructure-as-code and application deployments using Bicep, ARM, or Terraform.
• Administer and operate AI platforms including Azure AI Foundry, Azure OpenAI, Anthropic Claude, and OpenAI — managing model configurations, access controls, usage policies, evaluations, and production deployments.
• Administer and govern Model Context Protocol (MCP) integrations, ensuring access controls, authentication standards, data-handling boundaries, and usage policies are in place so AI platforms connect to enterprise systems securely and in compliance with bank standards.
• Manage and maintain APIs and event-driven services (App Service, Functions, API Management, Service Bus, Event Grid) that connect AI platforms and automations to business capabilities and install, configure and manage API security gateway
• Implement retrieval-augmented generation (RAG) patterns using Azure AI Search, vector stores, and embeddings against enterprise content.
• Administer and maintain automations built on Power Automate, Logic Apps, and Copilot Studio that streamline operational tasks and integrate Microsoft 365, Teams, SharePoint, and ServiceNow.
• Engineer landing zones, networking, and identity integration (Entra ID, Conditional Access, managed identities, Key Vault) for new and existing Azure workloads.
• Implement AI governance and responsible-use guardrails: content filters, model and prompt evaluation, logging, cost controls, data-handling boundaries, and human-in-the-loop review.
• Define cloud governance through Azure Policy, RBAC, tagging, cost management, and observability in Azure Monitor, Log Analytics, and Application Insights.
• Document reference patterns, pipeline templates, and runbooks; mentor teammates on cloud infrastructure, AI platform administration, and responsible AI usage.
• Administer and govern Microsoft Fabric environments — managing tenant and capacity settings, workspace permissions, data access controls, and usage monitoring across Fabric workloads including Data Factory, Lakehouse, and Real-Time Analytics, in alignment with bank security and compliance standards
• Serve as a technical reviewer on the Change Advisory Board for cloud and AI changes and provide engineering support for major incidents and planned releases.
• Provide metrics (KPIs and KRIs) as necessary related to various business processes

Required Qualifications

• 5+ years in cloud or software engineering, with at least 3 years hands-on building and operating workloads in Microsoft Azure.
• Production experience with core Azure services: virtual networking, App Service, Functions, API Management, Entra ID, Key Vault, Storage, and monitoring.
• Hands-on experience administering AI platforms such as Azure AI Foundry, Azure OpenAI, Anthropic Claude, and OpenAI — including model configuration, access management, usage monitoring, and production operations.
• Working knowledge of the Model Context Protocol (MCP) or comparable AI integration patterns, and a clear understanding of how to safely connect and govern enterprise systems exposed to AI platforms.
• Strong API engineering skills: designing, securing, and consuming REST APIs, with practical experience integrating third-party and internal services.
• Experience building CI/CD pipelines in Azure DevOps or GitHub Actions and authoring infrastructure-as-code with Bicep, ARM, or Terraform.
• Strong scripting skills in PowerShell and Python.
• Solid grasp of identity, networking, and security fundamentals in Azure, including Entra ID, Conditional Access, and zero-trust principles.
• Strong written and verbal communication. Able to translate cloud and AI concepts into clear options and tradeoffs for engineers, stakeholders, and leadership.
• Bachelor’s degree in Computer Science, Information Systems, or equivalent experience.

Preferred Qualifications

• Microsoft certifications such as Azure Administrator Associate (AZ-104), Azure Solutions Architect Expert (AZ-305), or DevOps Engineer Expert (AZ-400).
• Experience administering or operating production AI assistants, copilots, or RAG systems using Azure AI Search, vector databases, and evaluation frameworks.
• Experience administering and operating MCP servers that integrate AI platforms with enterprise data and tools.
• Experience integrating Power Automate, Logic Apps, or Copilot Studio with ServiceNow, Salesforce, or core banking platforms.
• Experience with containers and orchestration (AKS, Container Apps) and event-driven architectures.

Prior experience in financial services, banking, or another regulated industry, including familiarity with audit and change-management co