AI Engineering Productivity Manager Semiconductor

AI Engineering Productivity Manager Semiconductor Engineering Excellence | AI Transformation | Developer Productivity Location: Bengaluru / Hyderabad / Pune / Noida, India Work Mode: Onsite / Hybrid Experience: 10 18 Years Industry: Semiconductor | Artificial Intelligence | Engineering Productivity | Digital Transformation Role Overview We are seeking an experienced AI Engineering Productivity Manager to lead the adoption of Artificial Intelligence across semiconductor engineering organizations with the objective of improving engineering productivity, accelerating product development, and enabling intelligent automation. This strategic leadership role focuses on applying Generative AI, Large Language Models (LLMs), AI Agents, Engineering Copilots, Knowledge Management, and Workflow Automation across RTL Design, Physical Design, Verification, DFT, Process Engineering, Manufacturing, Test, Product Engineering, CAD, and Software Development teams. The successful candidate will work with Engineering Leadership, Digital Transformation, IT, AI/ML, CAD, EDA, Product Engineering, Manufacturing, and Operations teams to build an AI-first engineering ecosystem that significantly improves productivity, quality, collaboration, and innovation. Key Responsibilities Define and execute enterprise-wide AI Engineering Productivity strategy for semiconductor engineering organizations.Identify engineering workflows that can be accelerated using Generative AI, LLMs, AI Agents, and intelligent automation.Lead deployment of AI Engineering Copilots supporting RTL Design, Physical Design, Verification, DFT, Process Engineering, Manufacturing, Test, and Product Engineering.Develop AI-enabled solutions for code generation, design documentation, engineering search, report generation, debugging, design reviews, knowledge reuse, and technical documentation.Collaborate with EDA, CAD, Design, Manufacturing, Data Engineering, and Software teams to integrate AI into existing engineering workflows.Define engineering productivity KPIs including design cycle reduction, automation coverage, engineering efficiency, knowledge reuse, and development velocity.Lead adoption of AI-powered engineering platforms including Knowledge Graphs, RAG, Enterprise Search, AI Agents, and Digital Engineering tools.Build governance frameworks for AI adoption, security, IP protection, compliance, and responsible AI usage.Evaluate emerging AI technologies and identify opportunities to improve semiconductor engineering operations.Drive AI change management, user adoption, training, and continuous improvement initiatives.Partner with executive leadership to define long-term AI engineering roadmap and digital transformation strategy.Mentor cross-functional engineering teams and promote AI best practices across the organization.Measure business impact using engineering productivity, quality, cost, and innovation metrics. Required Qualifications Bachelor's or Master's degree in Electronics Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Software Engineering, or a related discipline. MBA is an advantage.10 18 years of experience in Semiconductor Engineering, Engineering Management, Digital Transformation, AI Platforms, EDA, CAD, or Enterprise Software.Strong understanding of semiconductor product development lifecycle.Proven experience leading engineering productivity or enterprise transformation initiatives.Experience implementing AI technologies within engineering organizations is highly desirable. Technical Skills Artificial Intelligence Generative AILarge Language Models (LLMs)AI AgentsAgentic AIRetrieval-Augmented Generation (RAG)Prompt EngineeringEngineering CopilotsKnowledge GraphsAI Workflow AutomationEnterprise AI Platforms Semiconductor Engineering RTL DesignASIC / SoC DesignPhysical DesignDesign VerificationDFTStatic Timing AnalysisEDA AutomationManufacturing EngineeringYield EngineeringProduct EngineeringCAD MethodologySemiconductor Design Flow Engineering Productivity Workflow AutomationEngineering AnalyticsDigital EngineeringKnowledge ManagementProcess ImprovementLean EngineeringAgile DevelopmentDevOpsEngineering MetricsContinuous Improvement Programming & Integration PythonSQLJavaREST APIsGitLinuxShell Scripting AI Frameworks LangChainLlamaIndexHugging FaceOpenAI APIsNVIDIA NeMo / NIMCrewAIAutoGenMLflowVector Databases Cloud & Infrastructure AWSMicrosoft AzureGoogle Cloud PlatformKubernetesDockerDatabricksSnowflakeCI/CDMLOpsLLMOps Enterprise Platforms JiraConfluenceGitHubGitLabSharePointServiceNowEngineering Knowledge PlatformsPLMMESERP AI Engineering Productivity Manager Semiconductor Engineering Excellence | AI Transformation | Developer Productivity Location: Bengaluru / Hyderabad / Pune / Noida, India Work Mode: Onsite / Hybrid Experience: 10 18 Years Industry: Semiconductor | Artificial Intelligence | Engineering Productivity | Digital Transformation Role Overview We are seeking an experien