Azure Cloud Engineer, AI & Automation
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Job description
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., * 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
Requirements
Do you have experience in Zero Trust security?, Do you have a Bachelor's degree?, Proven reliability: We always ground our innovation in our deep experience and strong financial foundation, so we are a partner you can trust., * 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., * 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