India
9 days ago
Technical Architect

A key responsibility is integrating a Retrieval Augmented Generation (RAG) model with our data-centric architecture platform to answer complex queries on best-in-class process planning and optimized layout generation. This role will leverage generative AI and RAG for design optimization, knowledge retrieval, and improved decision-making, while integrating real-time data (eventually feeding into MES), implementing a robust systems engineering approach, and ultimately bridging the gap between digital design and physical manufacturing. The successful candidate will have extensive experience in virtual manufacturing, data-centric architectures, and RAG model implementation. This is a highly impactful leadership role shaping our future manufacturing capabilities.

Bachelor's degree in Mechanical or Computer Science, Engineering, or a related field; advanced degree preferred. 12+ years of experience in software architecture and implementation, with a strong focus on virtual manufacturing and digital twin technologies. Experience with handing off virtual manufacturing outputs to a physical MES is highly desirable. Extensive experience with CAD/CAM systems, simulation tools, and ideally Teamcenter PLM. Understanding of IIoT principles in relation to virtual environments is beneficial. Proven experience leading the design and implementation of data-centric architectures within a virtual manufacturing context. Deep understanding of Systems Engineering principles and methodologies. Strong experience with data modeling and integration techniques within a virtual manufacturing environment. Experience with cloud-based platforms (AWS, Azure, GCP) is highly desirable. Extensive experience in designing, developing, and deploying RAG models, with a proven ability to integrate them with existing data factory. Deep understanding of various RAG architectures (e.g., vector databases, knowledge graphs) is essential. Experience in optimizing RAG models for specific use cases. Excellent communication, collaboration, and leadership skills. Lead the design and implementation of a real-time digital twin integration strategy for virtual manufacturing, integrating data from various sources (CAD/CAM systems, simulation tools, IIoT devices from virtual environments, eventually feeding into Teamcenter PLM and MES) into a unified digital twin environment. Architect solutions for data ingestion, processing, and visualization within the virtual environment. Design, develop, and implement the integration of a RAG model with our existing data-centric architecture platform. This will involve selecting an appropriate RAG framework, defining the knowledge base structure (potentially leveraging existing data within our platform), and developing the necessary interfaces and algorithms to enable the system to answer queries related to best-in-class process planning and optimized layout generation. This requires a deep understanding of our existing data architecture, data models, and data quality. Develop and optimize the RAG model's performance and accuracy, including ongoing monitoring and evaluation of the model's responses, iterative refinement of the knowledge base, and implementation of strategies to ensure the model's outputs align with our business goals. Champion the deployment and integration of Siemens GenAI Xcelerator and the integrated RAG model within the virtual manufacturing environment. This involves identifying appropriate use cases, developing integration strategies with existing systems (Teamcenter, simulation tools, knowledge bases, etc.), and overseeing the implementation and ongoing optimization of generative AI models and RAG for design reuse, process optimization, virtual commissioning, and enhanced knowledge retrieval and application. This will require collaboration with internal and external stakeholders and exploration of suitable RAG frameworks and knowledge base structures. Develop and implement an AI-driven system for reusing existing layouts within the virtual manufacturing context, leveraging machine learning algorithms to identify and apply relevant past designs from virtual models to accelerate the engineering process for new products, maximizing the value of past investments. This includes the development of data pipelines and algorithms to support this functionality within the virtual environment. Industrialize Siemens Dimensional Planning and Verification within the virtual manufacturing workflow, integrating this system seamlessly with the existing SYSML model from MagicDraw using a data-centric architecture. Ensure seamless handoff of verified designs to the physical manufacturing process. Implement a Systems Engineering approach to failure modes avoidance within the virtual environment, transitioning from a manual "digital paper" process to a more systematic approach leveraging Systems Engineering principles to optimize verification, reducing gaps and eliminating redundancy within the virtual manufacturing workflow. This includes developing and implementing processes and tools to support model-based systems engineering (MBSE) within the virtual environment. Ensure that failure modes are identified and mitigated before the design is handed off to physical manufacturing. Mentor and guide a team of engineers, providing technical leadership and guidance to the team, ensuring adherence to best practices and standards.
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