Must Have Technical/Functional Skills
Must Have Experience :
• 10+ years in data / analytics architecture, with strong manufacturing or industrial experience
• 3+ years designing and deploying AI/ML and/or GenAI solutions in production
• Hands on experience with plant data, time series analytics, and OT/IT integration
• Strong consulting skills: structured problem solving, executive communication, workshop facilitation
Preferred Skills
• Cloud platforms (Azure / AWS / Google Cloud Platform), Databricks or Snowflake
• Streaming (Kafka / Event Hubs), ML platforms (MLflow, Azure ML, SageMaker)
• GenAI platforms (Azure OpenAI, Bedrock, Vertex AI) and vector databases
• Exposure to digital thread, smart factory, or digital twin initiatives
Roles & Responsibilities
Background : We are looking for an AI & Data Architect with strong manufacturing domain expertise and consulting mindset to help industrial enterprises design, deploy, and scale data and AI platforms across plants and enterprise systems. This role bridges operations, engineering, and IT, translating manufacturing priorities into secure, governed, and production grade AI solutions that deliver measurable business outcomes.
Travel: 25–50% (plants, client workshops, exec reviews)
What You Will Do
• Lead plant to enterprise discovery workshops with Operations, Engineering, Quality, Supply Chain, and IT leaders
• Develop Solutions to respond to RFQ from the manufacturing customers
• Translate manufacturing challenges into AI use cases (predictive maintenance, quality, yield, throughput, inventory, service)
• Architect OT + IT data platforms integrating historians, MES, ERP, and cloud platforms
• Design and guide delivery of AI/ML and GenAI solutions (time series ML, computer vision, RAG based copilots)
• Define MLOps / LLMOps frameworks for industrial environments
• Create executive ready architectures, roadmaps, and value stories
• Act as a trusted advisor during plant visits, architecture reviews, and steering committees
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Core Architecture Focus
• OT/IT Integration: PLC/SCADA/DCS, historians (PI/Aveva), MES, ERP (SAP), PLM, QMS
• Data Platforms: Lakehouse, streaming/event-driven, time series architectures
• AI / GenAI: Predictive analytics, anomaly detection, computer vision, maintenance & operations copilots
• Security & Governance: Industrial cybersecurity awareness, data governance, responsible AI, human in the loop
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Key Deliverables
• Plant to enterprise AI & Data target architecture
• Manufacturing AI roadmap (pilot → scale across plants)
• Digital thread architecture linking design, production, quality, and service
Industrial MLOps / LLMOps framework
Executive level value realization dashboards
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