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PLM AI System Architect

Siemens Energy Industrial Turbomachinery India Private Limited · Gurgaon, Pune, India

About this role

The PLM AI System Architect will lead AI transformation of the Product Lifecycle Management (PLM) ecosystem, connecting engineering stakeholders, PLM platforms and enterprise AI architecture. The full-time role is listed in Gurgaon, Haryana, and Pune, Maharashtra, India.

Responsibilities

  • Drive AI adoption across the product lifecycle, including requirements, engineering and manufacturing bills of materials (EBOM/MBOM), CAD/CAM data, digital twins and service lifecycles.
  • Design and scale agentic, multi-agent systems that reason over PLM data, automate classification and assess the impact of engineering changes.
  • Architect retrieval-augmented generation (RAG) and AI-powered retrieval for both structured PLM attributes and relationships and unstructured specifications, PDFs and drawings, with engineering-grade accuracy.
  • Develop Model Context Protocol (MCP) servers and secure integration layers that make PLM services available to enterprise AI agents.
  • Define an AI maturity roadmap and ensure deployments meet enterprise standards for data privacy, intellectual property protection and cost governance. Establish reusable architecture patterns and pursue measurable reductions in cycle time and manual effort while maintaining accurate, trustworthy engineering outputs.

Requirements

  • At least 7 years of total experience, including 3 years in artificial intelligence, and a basic understanding of PLM.
  • Proven expertise in agentic AI frameworks, RAG architectures and tool-calling patterns, including grounding strategies to reduce hallucinations in technical settings.
  • Experience building AI integration layers such as MCP servers, managing APIs and microservices, and deploying AI services in cloud-native environments.
  • Ability to communicate complex technical architecture as actionable business value to senior leadership.

Skills for this role

Product Lifecycle Management (PLM)Generative AIAgentic AIMulti-agent systemsRetrieval-augmented generation (RAG)Model Context Protocol (MCP)Tool callingAI groundingAPIsMicroservicesCloud-native deploymentEBOMMBOMCAD/CAMDigital twinsChange impact analysisData privacyIP protectionTechnical communication

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