Lead Engineer - Digital Design
What You’ll Do
The Lead Engineer will provide technical leadership in defining and executing the Digital Design technology strategy, driving capability development to support the Digital Engineering organizations vision of achieving zero engineering lead time. Primary responsibility of this role is to lead the development of the Digital Design technology roadmap and align it with the needs of key business stakeholders.
The individual will be expected to collaborate closely with cross-functional teams within the Modeling & Simulation organization, as well as with product stakeholders, to develop and deploy impactful Digital Design solutions that support key NPI and NTI programs. The role also requires identifying emerging technologies, fostering innovation, and ensuring successful adoption of digital engineering capabilities across the organization.
Job Responsibilities Would Include
- Lead Digital Design Deployment for Strategic Programs
Serve as the Technical Lead/Project Lead for Digital Design solution development and deployment across key NPI/NTI programs. Drive initiatives that enable 2x engineering design speed, reduce product development costs, and support Product Line strategic objectives.
- Drive Advanced AI/ML Capability Development
Lead capability development programs focused on applying advanced AI and Machine Learning techniques in engineering, including Scientific Machine Learning (SciML), Generative AI, Reduced Order Modeling (ROM), and AI-enabled vertical integration of engineering models.
- Shape the Long-Term Digital Design Technology Roadmap
Partner with business and technology leadership teams to define and execute the long-term Digital Design technology roadmap. Key focus areas include: Multi-Objective and Multi-Disciplinary Design Optimization (MDO), AI/ML and SciML-based hybrid models, Geometric Deep Learning, Generative Design, RAG and LLM-based workflows for Engineering and RFQ processes
- Develop Strategic Technical Proposals
Collaborate closely with Product Engineering and Digital Engineering teams to develop compelling technical proposals that address business challenges and accelerate technology adoption.
- Drive Technology Scouting and Contemporary Thinking
Continuously monitor and evaluate emerging advancements in AI/ML for physics-based engineering applications. Identify, assess, and facilitate adoption of relevant technologies that create competitive advantages for Eaton.
- Champion DFSS Adoption and Execution Excellence
Lead the implementation of DFSS methodologies within Digital Design initiatives for NPI programs. Mentor teams, support Green Belt reviews, and promote data-driven decision-making to improve project outcomes.
- Foster a Culture of Continuous Improvement
Drive continuous improvement initiatives focused on improving Cost, Quality, and Schedule performance through effective application of ECIS tools, methodologies, and best practices.
- Mentor and Develop Engineering Talent
Coach and mentor engineers to ensure high-quality technical execution, foster innovation, and accelerate professional growth within the team.
- Build and Strengthen the Digital Design Ecosystem
Represent Eaton in external forums, industry conferences, and technology consortiums. Establish and nurture collaborations with ecosystem partners, research institutions, and universities to accelerate innovation and capability development.
Qualifications
Masters degree in Engineering
Relevant experience: 8+ years with Masters degree / 5+ years with PhD - Demonstrated experience in Modeling & Simulation, coupled with strong expertise in AI/ML model development and deployment. Proven ability to apply machine learning, scientific machine learning (SciML), and data-driven techniques to solve complex engineering problems and accelerate product development.
Skills
Technical Skills
Advanced Modeling & Simulation
- Expertise in physics-based modeling and multiphysics simulation at component, subsystem, and system levels using ANSYS, ABAQUS, DIGIMAT, MATLAB, and similar tools.
Optimization & Engineering Workflows
- Experience developing integrated workflows for simulation-driven design, multi-objective optimization, and design exploration using modeFRONTIER, iSight, VOLTA, or equivalent platforms.
AI/ML for Engineering Applications
- Strong hands-on experience in Machine Learning, Deep Learning, and AI-driven engineering solutions including SciML, PINNs, Digital Twins, surrogate models, and generative AI for simulation and design optimization.
Agentic AI, LLMs & Digital Engineering
- Experience building Agentic AI, LLM, and RAG-based solutions using Azure AI, Azure OpenAI, LangChain, LangGraph, Semantic Kernel, Vector Databases, and Knowledge Graphs to automate engineering processes.
Technical Leadership & Innovation
- Proven track record in technology innovation, patents/IP generation, project leadership, stakeholder management, and driving continuous improvement through Lean, Agile, and DFSS methodologies.
Soft Skill
Accountability: Owns challenges and delivers results.
Passion & Drive: Self-motivated, proactive, and goal-oriented.
Collaboration: Builds relationships and works effectively across teams.
Strategic Mindset: Aligns technology decisions with business goals.
Problem Solving: Analyzes complex issues and delivers effective solutions.