About The Position

End-to-End AI Product Delivery: Lead the project management lifecycle for AI/ML applications, from initial concept and requirement gathering to deployment and global scaling within the Digitalization and Transformation department. Domain-Driven AI Development: Apply deep subject matter expertise in Requirements Engineering, MBSE, and FMA to guide the development of AI tools, ensuring they adhere to industry standards (e.g., EARS, INCOSE, SAE J1739). Lead Intelligent Search & Retrieval Projects: Deliver AI solutions that provide instant access to critical data, regulatory information, and program live-data, integrating guides for enterprise tools like FEDE and 3DX to improve engineering efficiency. Drive NLP & Requirements Refinement Tools: Manage the development of AI-driven "refactoring" tools that use Natural Language Processing to ensure engineering requirements are compliant, concise, and seamlessly integrated with tools like FEDE WB, Jama, and MagicDraw. Automate FMA Workflows: Lead the delivery of generative AI tools designed to automate Failure Mode Avoidance, transforming boundary diagrams into SysML models or optimized DFMEAs to reduce manual effort and ensure consistency. Agile Product Leadership: Work with IT matched-pair product teams and data scientists to specify AI tool functionalities, prioritize the product backlog, and manage delivery within an Agile framework. D&R Integration & Deployment: Ensure AI tools are practical for the Design and Release (D&R) engineering community, managing the rollout and implementation of these tools into active vehicle programs. Change Management & Training: Develop tool documentation and lead training sessions to help functional engineering teams transition from manual processes to AI-augmented workflows. Established and active employee resource groups

Requirements

  • BS in Engineering is required.
  • 5+ years of experience in Product Development, specifically within Design and Release (D&R) or Systems Engineering.
  • Proven Project Management experience leading technical software or digital tool implementations from inception to launch.
  • Strong foundational knowledge in MBSE (SysML), Requirements Management, and FMA processes.
  • Experience with industry-standard tools: Siemens Teamcenter (FEDE), CatiaMagic (Cameo), and/or Dassault 3DX.
  • Demonstrated interest or experience in AI/ML applications (e.g., Large Language Models, NLP, or Data Automation) as applied to engineering problems.
  • Strong interpersonal skills with the ability to translate complex engineering needs into technical requirements for AI developers.
  • Strong verbal and written communication skills for presenting digital strategies to leadership.
  • Proficient in Microsoft Office tools and Agile management software (e.g., Jira, ADO).

Responsibilities

  • Lead the project management lifecycle for AI/ML applications, from initial concept and requirement gathering to deployment and global scaling.
  • Apply deep subject matter expertise in Requirements Engineering, MBSE, and FMA to guide the development of AI tools, ensuring they adhere to industry standards.
  • Deliver AI solutions that provide instant access to critical data, regulatory information, and program live-data, integrating guides for enterprise tools like FEDE and 3DX to improve engineering efficiency.
  • Manage the development of AI-driven "refactoring" tools that use Natural Language Processing to ensure engineering requirements are compliant, concise, and seamlessly integrated with tools like FEDE WB, Jama, and MagicDraw.
  • Lead the delivery of generative AI tools designed to automate Failure Mode Avoidance, transforming boundary diagrams into SysML models or optimized DFMEAs to reduce manual effort and ensure consistency.
  • Work with IT matched-pair product teams and data scientists to specify AI tool functionalities, prioritize the product backlog, and manage delivery within an Agile framework.
  • Ensure AI tools are practical for the Design and Release (D&R) engineering community, managing the rollout and implementation of these tools into active vehicle programs.
  • Develop tool documentation and lead training sessions to help functional engineering teams transition from manual processes to AI-augmented workflows.
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