Back
Mid-level AI role in a metro city at a known global industrial firm with broad skills required.
AI solution engineering skills transfer across industries, though engineering domain experience is preferred.
Explicit 4–7 year requirement plus mandatory Azure, Python, and AI workflow skills make screening strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, test, and deploy AI-enabled tools embedded in engineering workflows to improve efficiency and consistency in operational processes such as engineering planning, NPI execution, and DFMEA/PFMEA.
Develop end-to-end AI solutions including prompt logic, data preparation, workflow orchestration, and integration into Microsoft Teams, SharePoint, or existing engineering tools using Azure OpenAI and Eaton-approved AI frameworks.
Collaborate with EFE Digital and IT teams to ensure compliance with security, logging, auditability, and Eaton AI deployment standards, while piloting and iterating solutions based on engineering user feedback to drive adoption.
Bachelor’s degree in Computer Science, Engineering, or related field; Master’s degree in AI, Machine Learning, or Data Science preferred.
4-7 years of experience in software development, automation, or digital solution engineering.
Hands-on experience with Python, APIs, cloud services, and preferably the Azure environment.
Not explicitly mentioned: notice period or strict location requirements.
Experienced at developing full-cycle AI solutions that move beyond proofs of concept to production-ready deployments within engineering or industrial contexts.
Familiar with engineering operational processes such as NPI, project management, quality, DFMEA/PFMEA, and able to translate process needs into technical requirements and user stories.
Capable of working cross-functionally with process owners, IT, and digital teams to embed AI tools into existing workflows while ensuring compliance with organizational security and deployment standards.