Lead Azure Infrastructure Engineer

In your career, let’s prove what’s possible.

At Lam Research, we create equipment that drives technological advancements in the semiconductor industry. Our innovative solutions enable chipmakers to power progress in nearly all aspects of modern life, and it takes each member of our team to make it possible.

Across our organization, our employees come to work and change the world. We take on the toughest challenges with precision and accuracy. We push for the next big semiconductor breakthrough. We lead the way in one of the most critical and fast-moving industries on the planet. And we do it together, with deep connections and limitless collaboration.

The impact we have on the world is made possible by focusing on our people. So we recognize and celebrate our teams’ achievements. We strive to create an inclusive and diverse culture where everyone’s contribution and voice has value. We evaluate and evolve our offerings, so our people receive the support and empowerment to do meaningful things for their lives, careers, and communities.

Because at Lam, we believe that when people are the priority and they’re inspired to unleash the power of innovation for a better world together, anything is possible.

Date:
Jul 16, 2026

Location:

Fremont, CA, US, 94538

Worker Category:
On-site Flex

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. As a hands-on technical lead, you will define and implement platform architecture, infrastructure patterns, automation, and operational readiness for Azure-based AI services, helping accelerate delivery of Enterprise AI initiatives at scale.

• 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, Power Shell, 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.

Minimum Qualifications:

• 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 Power Shell
  .
• 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…