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Lam Research’s LIDAS (Lam India Data Analytics & Sciences) team works with Global Operations on enterprise applications, automation, analytics, and AI-driven solutions. This Bangalore-based role leads the design and delivery of scalable applications intended to improve operational efficiency, decision-making, workflows, and quality in semiconductor manufacturing and supply chain operations.
Responsibilities
Architect end-to-end applications that integrate AI capabilities, enterprise systems, automation platforms, cloud services, and data sources such as SQL Server, Lakehouse, and Data Lake environments. Define components, APIs, integrations, and data flows with attention to performance, security, maintainability, and scalability.
Work with business stakeholders to translate challenges and requirements into technical solutions. Lead proofs of concept, guide development teams, conduct design reviews, and promote coding standards and architecture governance.
Drive adoption of Generative AI, Copilot, OpenAI/GPT-based solutions, automation, and cloud-native architectures. Collaborate with global teams using Agile, DevOps, and CI/CD practices; explain technical decisions, trade-offs, and roadmaps to technical and non-technical stakeholders.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field; 8+ years in enterprise application development, architecture, or solution delivery, including 4+ years leading large-scale application programs or enterprise solution initiatives.
Experience delivering enterprise applications on Azure, AWS, or GCP; hands-on expertise in one or more frameworks or technologies such as .NET, Angular, or Python; and experience integrating applications, APIs, automation solutions, and enterprise data platforms. Strong stakeholder management, communication, and technical documentation skills are required.
Preferred qualifications include implementing AI-enabled solutions with Generative AI, OpenAI, GPT, or enterprise AI platforms; knowledge of Microsoft Fabric, Lakehouse architectures, Data Lakes, and analytics ecosystems; and experience with Docker, Kubernetes, Azure DevOps, Git, Jira, and CI/CD. Exposure to Microsoft Power Platform, RPA, or intelligent automation; relevant semiconductor, manufacturing, supply chain, operations, or quality experience; and knowledge of integration patterns, security frameworks, OAuth, REST APIs, and JSON are also preferred.
The work location model is On-site Flex: at least three days per week on-site at a Lam or customer/supplier location, with the option to work remotely for the remaining days.
Enterprise application architectureGenerative AIOpenAIGPTMicrosoft CopilotSQL ServerAzureAWSGoogle Cloud Platform.NETAngularPythonAPI integrationMicrosoft FabricLakehouse architectureData LakesAgileDevOpsCI/CDDockerKubernetesAzure DevOpsGitJiraMicrosoft Power PlatformRobotic Process AutomationOAuthREST APIsJSONStakeholder management
Work arrangement
Hybrid
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