Lead Engineer - Operational Excellence ( AI Solutions)

About

The AI Solutions Engineer will design, build, test, and deploy AI enabled tools that improve the efficiency, consistency, and execution of Eaton’s engineering processes.

This role sits within Engineering Operational Excellence (EFE OPEX) and focuses on hands‑on development of AI solutions embedded directly into engineering workflows, such as engineering planning, NPI / Product Development tasks execution, DFMEA/PFMEA, engineering knowledge access, and reporting.

The role works closely with EFE Digital and IT to implement AI solutions using Eaton‑approved platforms and standards. The primary accountability is delivery and adoption of working AI tools that engineers use in their day‑to‑day work. This role does not own enterprise AI strategy or platform governance.

Responsibilities

• AI Solution Development (Primary Focus)

  • Design and hands‑on build AI solutions that support engineering operational processes, including:
    • Engineering planning and scheduling
    • NPI / PROLaunch execution support
    • DFMEA / PFMEA drafting and consistency checks
    • Engineering knowledge retrieval using RAG (with citations)
    • Design review action tracking and reporting
  • Implement AI workflows using Azure OpenAI, Azure AI Foundry, and Eaton‑approved AI frameworks.

• Implementation & Integration

  • Develop end‑to‑end AI solutions, including:
    • Prompt logic and AI agent workflows
    • Data preparation and retrieval
    • Basic orchestration and error handling
    • Integration into Microsoft Teams, SharePoint, or existing engineering tools
  • Partner with IT to ensure solutions comply with:
    • Security and identity requirements
    • Logging and auditability standards
    • Eaton AI guardrails and deployment practices

• Cross‑Functional Collaboration

  • Work closely with:
    • EFE Digital on AI capabilities embedded in engineering and PLM‑adjacent tools
    • IT on infrastructure, APIs, and deployment pipelines
  • Translate engineering process needs to clear technical requirements and user stories.

• Adoption & Continuous Improvement

  • Pilot AI tools with engineering users and collect feedback
  • Iterate solutions to improve usability, reliability, and value
  • Support basic documentation, demos, and user enablement activities

Qualifications

• Bachelor’s degree in computer science, engineering, or related field. A master’s degree in AI, Machine Learning, or Data Science is preferred.
• 4‑7 years of experience in software development, automation, or digital solution engineering

Skills

• Hands‑on experience with: Python, APIs and cloud‑based services, Azure environment (preferred)
• Demonstrated ability to build and deploy working solutions, not just proofs of concept

Preferred Qualifications

• Experience working in an engineering, industrial, or manufacturing environment
• Familiarity with:
  • Engineering workflows such as NPI, project management, quality, or documentation
  • AI assistants, RAG patterns, or workflow‑based AI solutions
• Comfortable working directly with process owners and end users

Additional Skills

• Strong analytical, problem‑solving, and data‑driven decision‑making skills
• Excellent communication ability to translate complexity into clear narratives
• Ability to collaborate in a global, cross‑functional engineering environment