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Engineering Systems Engineer – PLM & AI Enablement

Amphenol HSIO Yocumtown, Pennsylvania, United States

On-site Full-time
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Job Summary


The Engineering Systems Engineer – PLM & AI Enablement is responsible for supporting and improving Product Lifecycle Management (PLM), engineering data, and digital engineering systems across the organization.


This role will provide technical and operational support for Windchill PLM, engineering change processes, BOM and product structure management, user access, workflow troubleshooting, and system standardization. The position will also support AI-enabled engineering initiatives by improving data quality, enabling enterprise search, supporting AI tool integration, and helping identify practical AI use cases within engineering workflows.


The role requires close collaboration with global engineering, PLM, IT, and AI teams across China, India, the United States, and other locations.


Key Responsibilities


PLM System Support & Administration




  1. Windchill System Support

    Support daily operation of the Windchill PLM environment, including user account activation, role assignment, access permissions, and system configuration support.


  2. System Troubleshooting

    Investigate and resolve PLM-related issues including workflow interruptions, user access problems, system errors, data synchronization issues, and other functional abnormalities.


  3. Engineering Change Management

    Support and improve ECR, ECN, and engineering release processes within Windchill.


  4. BOM & Product Structure Management

    Support engineering BOMs, product structures, part data, material information, and related product lifecycle data within PLM.


  5. Engineering Document Management

    Support the creation, revision, approval, release, and control of engineering drawings, specifications, documents, and technical records.


  6. Creo / PLM Integration

    Support Creo and Windchill integration, including CAD data management, check-in/check-out processes, version control, release workflows, and user troubleshooting.


 


Engineering Data & Process Improvement




  1. Data Quality & Standardization

    Improve the accuracy, consistency, completeness, and structure of engineering data across PLM systems.


  2. Process Standardization

    Develop and maintain standardized procedures, work instructions, system documentation, and user guidelines for PLM and engineering systems.


  3. User Training & Support

    Provide training and technical support to engineering users and help improve system adoption and proper system usage.


  4. Continuous Improvement

    Identify opportunities to improve PLM workflows, engineering processes, system usability, automation, and data management practices.


 


AI & Digital Engineering Enablement




  1. PLM AI Readiness

    Support initiatives to prepare engineering data for AI-enabled applications by improving metadata, document structure, BOM quality, access controls, and data consistency.


  2. Enterprise Search Enablement

    Support implementation, testing, and improvement of enterprise search technologies used to retrieve engineering data, product information, technical documents, and organizational knowledge.


  3. AI Tool Integration

    Support integration and deployment of AI-enabled engineering tools with PLM and related engineering systems.


  4. AI Use-Case Development

    Work with engineering teams to identify practical AI applications involving engineering knowledge retrieval, product data, BOMs, documentation, engineering workflows, and technical support.


  5. Proof-of-Concept Support

    Participate in evaluation, testing, validation, and deployment of AI, search, and engineering-system proof-of-concept projects.


  6. Automation Opportunities

    Identify opportunities to use AI, workflow automation, and digital tools to reduce manual work, improve engineering productivity, and improve data quality.


 


Global Collaboration




  1. Global Engineering Support

    Collaborate with engineering, PLM, IT, and AI teams across global locations to resolve system and technical issues.


  2. Global Project Support

    Participate in global PLM, digital engineering, enterprise search, and AI implementation projects.


  3. Local Coordination

    Serve as a local technical point of contact for global engineering systems initiatives and coordinate system-related activities with local engineering teams.


  4. Cross-Functional Collaboration

    Work closely with engineering, manufacturing, quality, IT, product management, and other functions to ensure engineering systems effectively support business and product-development needs.


 


Job Requirements



  1. Bachelor's degree in Mechanical Engineering, Computer Engineering, Industrial Engineering, Information Systems, or a related technical discipline.

  2. Minimum 3 years of experience in PLM, engineering systems, product engineering, engineering data management, or a related technical role.

  3. Experience with Windchill PLM or a comparable Product Lifecycle Management platform.

  4. Knowledge of ECR/ECN processes, BOM management, product structures, engineering document control, and product data management.

  5. Experience with Creo or other CAD systems and familiarity with CAD-to-PLM integration.

  6. Understanding of engineering data structures, metadata, revision control, lifecycle states, access permissions, and workflow management.

  7. Strong technical troubleshooting and problem-solving skills.

  8. Strong English communication skills, including listening, speaking, reading, and writing, with the ability to participate effectively in global technical meetings.

  9. Strong documentation and process-development skills.

  10. Ability to collaborate effectively with global engineering, IT, and cross-functional teams.


 


Preferred Qualifications



  1. Experience supporting global Windchill or PLM environments.

  2. Experience with enterprise search, engineering knowledge management, or AI-enabled business applications.

  3. Familiarity with AI concepts, large language models, retrieval-based search, or AI-assisted engineering workflows.

  4. Experience with system integration, APIs, automation, or engineering software deployment.

  5. Experience in the electronics, connector, automotive, industrial, or high-tech manufacturing industries.

  6. Familiarity with engineering master data, ERP integration, and PLM-to-ERP data flows.


 


Key Competencies



  • Strong analytical and troubleshooting ability

  • Engineering systems mindset

  • Data-driven problem solving

  • Strong ownership and accountability

  • Ability to work independently

  • Strong global communication skills

  • Continuous improvement mindset

  • Ability to translate engineering needs into system and process improvements

  • Interest in emerging AI and digital engineering technologies