Lead Azure Infrastructure Engineer

About the role

In this role, you will directly contribute to Lam’s Enterprise AI strategy by building and scaling the Azure platform foundations that power secure, reliable, and production-ready AI services across the company.

Responsibilities

• Lead the design and implementation of Azure platform and infrastructure patterns that support Enterprise AI services, ensuring solutions are scalable, secure, maintainable, and ready for production use.
• Build and evolve Azure-based foundations for AI services, including networking, identity, access, connectivity, deployment patterns, and environment readiness across development and production landscapes.
• Partner with engineering teams to enable deployment and operation of AI services on Azure, including services related to Azure OpenAI, MS Foundry, Azure API Management, AKS/Kubernetes, and other Azure-native platform capabilities.
• Define and improve infrastructure automation, platform provisioning, and engineering workflows using Python, PowerShell, CI/CD pipelines, and infrastructure-as-code practices where appropriate.
• Build and enhance observability across Azure AI services using Application Insights, Azure Monitor, Log Analytics, KQL, dashboards, alerting, and health checks.
• Review platform and application architectures to improve operability, reliability, security, and supportability, and drive remediation of recurring technical and platform issues.
• Support production readiness through release validation, operational standards, runbooks, monitoring, and incident response for Azure-based AI services.
• Ensure platform controls, operational processes, and technical artifacts are audit-ready and aligned with enterprise compliance, resiliency, and recovery expectations.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
• Strong hands-on experience designing, building, and supporting cloud platforms in Microsoft Azure.
• Experience with Azure infrastructure and platform services, including areas such as networking, identity, monitoring, automation, deployment patterns, and production readiness.
• Experience with Application Insights, Azure Monitor, Log Analytics, and Kusto Query Language (KQL) for troubleshooting, telemetry analysis, and operational visibility.
• Strong scripting or automation experience using Python and/or bash and PowerShell.
• Experience with CI/CD pipelines, deployment automation, and production release practices.
• Experience reviewing technical architectures and driving implementation decisions for scalable and supportable cloud services.
• Strong communication skills with the ability to translate complex technical issues into clear updates and recommendations for engineering teams, stakeholders, and leadership.

Preferred Qualifications

• Experience with Azure AI services, including Azure OpenAI / Foundry or other AI/ML or generative AI platforms.
• Experience with Azure API Management, containerized services, and AKS/Kubernetes.
• Experience with private networking, DNS, access controls, and secure connectivity patterns in Azure.
• Experience with incident response, root cause analysis, observability, and operational support for production services.
• Experience working with enterprise ticketing or ITSM platforms such as Jira and ServiceNow.