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Senior Engineer - Operational Excellence (AI Solutions)

Eaton -
Pune, Maharashtra

Apply Now

Job details

Qualifications

BCS
Azure
Computer Science
Master's degree
Analysis skills
Project management
Bachelor's degree
Machine learning
SharePoint
Software development
APIs
Agile
Data science
Manufacturing
AI
Communication skills
Python
Data Science
Product lifecycle management

Full job description

What you’ll do:

Eaton announced, on January 26, 2026, the intent to separate its Mobility Group (including both the Vehicle and eMobility segments) into an independent, publicly traded company. We expect to complete the separation by the end of the first quarter of 2027. As a standalone company, the Mobility business will be more focused and agile, creating exciting opportunities for employees to grow, innovate, and help shape the future of mobility. The separation reflects strong confidence in the Mobility team and positions the new company as an employer of choice in the automotive and commercial vehicle industry.

The compensation and benefits that will initially be offered for this position are based on Eaton's plans, programs and practices. If you are offered and accept this position and are actively employed by the Mobility Group when the spinoff closes, the new company will provide further details to employees concerning compensation and benefits at that time.

Job summary

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.

Job responsibilities

AI Solution Development (Primary Focus)

Design and hands on build AI solutions that support engineering operational processes, including:

o Engineering planning and scheduling

o NPI / PROLaunch execution support

o DFMEA / PFMEA drafting and consistency checks

o Engineering knowledge retrieval using RAG (with citations)

o 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:

o prompt logic and AI agent workflows

o data preparation and retrieval

o basic orchestration and error handling

o integration into Microsoft Teams, SharePoint, or existing engineering tools

Partner with IT to ensure solutions comply with:

o security and identity requirements

o logging and auditability standards

o Eaton AI guardrails and deployment practices

Cross Functional Collaboration

Work closely with:

o EFE Digital on AI capabilities embedded in engineering and PLM adjacent tools

o 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:

o Engineering workflows such as NPI, project management, quality, or documentation

o AI assistants, RAG patterns, or workflow based AI solutions

Comfortable working directly with process owners and end users

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.

Apply Now

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