Azure Cloud Engineer – AI & Automation
Responsibilities:
• Create and support Azure-based solutions spanning infrastructure, connectivity, identity, storage, and managed platform services in line with enterprise architecture and security expectations.
• Develop and optimize deployment automation using infrastructure-as-code and modern release pipelines through tools such as Azure DevOps, GitHub Actions, Bicep, and Terraform.
• Operate and administer AI services across Azure AI Foundry, Azure OpenAI, Claude, and related platforms, including model setup, permission management, policy enforcement, evaluation, and live environment support.
• Establish and govern secure integrations for Model Context Protocol and connected enterprise systems by applying strong authentication, access controls, and data protection standards.
• Manage APIs, event-driven components, and security gateway configurations that enable AI services and automated workflows to connect with business applications reliably.
• Build retrieval-augmented AI solutions using Azure AI Search, embeddings, and vector-based data patterns to improve access to enterprise knowledge.
• Maintain and enhance automation solutions built with Power Automate, Logic Apps, and Copilot Studio, supporting integrations with Microsoft 365, Teams, SharePoint, and ServiceNow.
• Strengthen cloud governance through Azure Policy, tagging strategy, cost oversight, monitoring, logging, and operational observability tools such as Azure Monitor and Application Insights.
• Support Microsoft Fabric administration by overseeing tenant settings, workspace permissions, capacity controls, data access, and usage visibility across supported workloads.
• Contribute technical documentation, reusable standards, KPI/KRI reporting, change review activities, and incident or release support for cloud and AI environments.
Qualifications:
• At least 5 years of experience in cloud engineering or software engineering, including 3 or more years working directly with Microsoft Azure in production settings.• Strong hands-on knowledge of core Azure services such as virtual networking, App Service, Functions, Entra ID, Key Vault, Storage, and monitoring capabilities.
• Proven experience managing AI platforms in production, including Azure AI Foundry, Azure OpenAI, Claude, or comparable model services.
• Practical expertise with CI/CD implementation and infrastructure-as-code using tools such as Azure DevOps, GitHub Actions, Bicep, or Terraform.
• Familiarity with cloud governance, security controls, and compliance-focused operations in enterprise environments.
• Experience working with Azure-focused technologies and related tools, including Azure Stack, Azure DevOps, Microsoft Purview, and AI-enabled services.
• Ability to support API-driven integrations, automation frameworks, and event-based architectures used in modern cloud platforms.
Compensation
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