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Required Qualifications Education Bachelor's or Master's degree in Engineering, Computer Science, Industrial Engineering, Data Science, or related field. Experience 7+ years of experience in Manufacturing, Industrial Operations, Digital Manufacturing, Industry 4.0, or Industrial Digital Transformation. 3+ years designing and deploying AI, Analytics, Machine Learning, or GenAI solutions. Experience leading large-scale enterprise transformation programs. Strong client-facing consulting and solution architecture experience. Required Technical Skills AI & Advanced Analytics Generative AI and Large Language Models (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.) Agentic AI and Multi-Agent Architectures Machine Learning and Predictive Analytics Computer Vision Time-Series Analytics Knowledge Graphs (Neo4j preferred) RAG Architecture and Vector Databases Cloud & Data Platforms Microsoft Azure AI Services Azure Data Platform Databricks Microsoft Fabric AWS or Google Cloud AI Platforms Data Engineering and Data Governance Industrial & Manufacturing Systems MES (AVEVA, Siemens Opcenter, Rockwell, Dassault, SAP ME) SCADA, DCS, PLC Ecosystems Historians (PI, IP21, Canary) ERP (SAP, Oracle) PLM and Engineering Systems IIoT Platforms Architecture & Engineering Enterprise Architecture Solution Architecture API and Integration Design MLOps / LLMOps AI Governance & Responsible AI Cybersecurity for Industrial Environments Preferred Qualifications Experience in Manufacturing Copilots, Operations Copilots, or Engineering Assistants. Experience with Digital Twin platforms and simulation technologies. Certifications in Azure AI, Azure Solutions Architecture, AWS ML, or equivalent. Experience working with industrial data platforms such as Cognite, AVEVA CONNECT, or DataHub platforms. Familiarity with autonomous operations and closed-loop optimization systems. Key Competencies Strategic Thinking Executive Communication Consultative Problem Solving Innovation Mindset Cross-Functional Leadership Architecture Governance Manufacturing Domain Expertise Stakeholder Management Business Value Realization Success Metrics AI solutions successfully deployed into production. Measurable client outcomes such as productivity improvement, cost reduction, quality enhancement, and operational efficiency gains. Growth of AI-driven business pipeline and revenue. Development of reusable assets and industrial AI accelerators. Increased adoption of AI across manufacturing and industrial operations. Client satisfaction and executive stakeholder trust. Ideal Profile A visionary technology leader who understands both the factory floor and the AI frontiercapable of transforming industrial operations through scalable, responsible, and outcome-driven AI solutions. .