Senior Specialist - AI Strategy (Mobility)

## What you’ll do:

Eaton announced, on June 11, 2026, the intent to combine its Mobility Group (including both the Vehicle and eMobility segments) with a new company. We expect to complete this process by the end of the first half of 2027. 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 transaction closes, the new company will provide further details to employees concerning compensation and benefits at that time.

Major purpose:

Define, develop, and deploy the vision and execution of enterprise AI platforms by leading high‑performing AI, data, and platform engineering teams to deliver reusable, cloud‑native ML and GenAI capabilities. The role enables AI‑driven insights, automation, and decision support across Mobility products and engineering workstreams spanning connected systems, electromechanical products, vehicle platforms, manufacturing, lifecycle management, NPI, NTI, and VAVE initiatives.

Job Description:

• Define and drive the AI engineering strategy to deliver enterprise‑grade, production‑ready AI capabilities that create measurable business impact across Mobility products, mechanical systems, and automotive platforms.
• Build and evolve a scalable, cloud‑native AI platform—encompassing ML and LLM‑powered services, shared infrastructure — to serve as a foundational layer across the Mobility product portfolio & workstreams
• Own the end‑to‑end AI technology lifecycle at a platform level, establishing standards and operating models for model development, deployment, monitoring, governance, scalability, and cost efficiency.
• Enable development of reusable AI services that support predictive insights, anomaly detection, design optimization, diagnostics, and operational intelligence across Mobility engineering and product teams.

Key Responsibilities:

• Define and own the long‑term strategy, architecture, and roadmap for the AI platform, aligned with Mobility product vision and business priorities.
• Build, lead, and develop AI, data, and platform engineering teams with strong exposure to mechanical systems, automotive data, and connected product ecosystems.
• Translate Mobility product strategy, engineering challenges, and operational goals into a clear, executable AI platform backlog with well‑defined releases and milestones.
• Drive standardization through shared services, reference architectures, and best practices to accelerate innovation and reduce fragmentation.
• Partner closely with Product Management, Engineering, Manufacturing, Digital, DevOps, and Data Science leaders to enable AI‑driven decision‑making across the product lifecycle.
• Ensure the AI platform meets enterprise standards for security, compliance, reliability, scalability, and cost efficiency.

## Qualifications:

Education –

• BE / B.Tech (Mechanical, Electrical, Automotive, Mechatronics, or related discipline preferred)
• Certification programs in AIML
• Master’s degree (Mechanical, Electrical, Automotive, Mechatronics, or related discipline preferred)

Experience-

• 15 to 20 Years of experience

Skills, Abilities, Knowledge –

• 15+ years of experience with significant exposure in enabling AI in business and driving impact through mainstreamed AI practices for various business workstreams
• Strong experience in identifying, developing, and deploying AI solutions for engineering analytics, product intelligence, diagnostics, optimization, or operational insights..
• Demonstrated ability to articulate AI impact using before‑and‑after comparisons tied to engineering efficiency, reliability, quality, cost, or performance metrics
• Excellent verbal and written communication skills with all levels of the organization.
• Uses comprehensive knowledge and skills to act independently while guiding and training others on analyzing the business requirements & AI application.
• Ability to independently drive complex initiatives while guiding teams on translating mechanical or automotive problems into AI solutions
• Experience working globally, understanding of agile delivery practices

## Skills:

Skills & Competencies:

• Strong expertise in AI/ML engineering, Generative AI, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), and agentic AI workflows.
• Proven experience building and operating data platforms, including large‑scale data pipelines, embeddings pipelines, and analytics systems.
• Experience building data and analytics platforms handling sensor data, telemetry, time‑series data, engineering logs, manufacturing data, and field performance signals.
• Hands‑on experience with cloud‑native and hybrid architectures supporting industrial, automotive, and connected‑product ecosystems.
• Demonstrated platform and architectural leadership, with the ability to define reference architectures and guide complex technical decisions.
• Established people leadership capabilities, including leading, mentoring, and scaling high‑performing engineering teams.
• Strong cross‑functional leadership skills, with experience working closely with Product, Platform, DevOps, and Data Science stakeholders.

Competencies –

• Mobility & Engineering Insight Generation – Applies AI to generate actionable insights across vehicle systems, electromechanical products, manufacturing operations, and field performance.
• Strategic mindset – Ability to strategically build pipeline of AI use cases in collaboration with the team and global leaders
• Cultivates innovation – Creating new and better ways for the organization to be successful in AI enbablement
• Communicates effectively - Developing and delivering multi-mode communications that conveys the need, value propositions & impact of AI use cases and enablement for Mobility business.
• Developing others: Influences development & upskilling of teams for AI knowledge & application.