Staff Mechanical Product Development Engineer- Integrated Predictive Analysis

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. 

Job Overview

As a Staff Mechanical Product Development Engineer- Integrated Predictive Analysis in the Mechanical Center of Excellence, you will lead advanced mechanical research, design, and validation efforts for cutting-edge interconnect systems used in AI data centers, high-performance computing, and next-generation communication infrastructure.

Your role involves developing novel mechanical structures, executing thermomechanical simulations, validating materials, and collaborating cross-functionally to enhance product performance, reliability, and manufacturability. You will operate with a high degree of autonomy and technical depth to define and drive innovation across mechanical platforms—from early-stage PoCs through NPI handoff.

This role is highly cross-functional, requiring collaboration with electrical, signal integrity, system architecture, manufacturing, and supplier development teams.

 

BU Overview

Consumer, network, and data center applications change at an exponential pace and the Data & Devices (D&D) business unit at TE Connectivity is at the heart of a continuously expanding connected life. Accordingly, we provide responsive, iterative, and fundamentally agile capabilities and conceive, design, and manufacture to support today's demands. Our customers are building the devices and the infrastructure that is redefining what information technology means. Our products push markets and meet the ever-changing needs of the evolving, more connected, data-driven world. We are enhancing how we do business, focusing on the most important things and staying agile and responsive to the needs of a faster, more connected world.

 

The Mechanical Center of Excellence (ME COE) plays a critical role in shaping the future of thermomechanical design, reliability engineering, and platform-based product development. By integrating advanced mechanical research, simulation, and manufacturability expertise, ME COE empowers faster, more scalable, and more robust innovation across TE’s high-speed connectivity and AI infrastructure portfolios.

Responsibilities

1. Strategy & Architecture 

• Define and drive system-level simulation architecture for integrating design, materials, and manufacturing processes (forming, molding, assembly) into unified digital workflows. 
• Influence product and technology roadmaps, embedding integrated predictive simulation, robustness, and digital engineering into next-generation data center, interconnect, and power delivery platforms. 

 

2. Simulation Method Development & Design Enablement 

• Develop and deploy integrated predictive engineering methodologies, combining product design, manufacturing simulation, and multiphysics analysis to enable robust, first-time-right solutions for complex electro-mechanical systems (connectors, high-speed I/O, enclosures, power-dense assemblies). 
• Drive design optimization and robustness using multi-disciplinary optimization (MDO), design space exploration, sensitivity analysis, and tolerance-aware design. 
• Establish predictive design frameworks including reduced-order models (ROMs), compact models, and digital twins linking simulation, test, and field performance. 

 

3. Physics-AI & Workflow Automation 

• Drive adoption of Physics-AI approaches combining simulation data, test data, and machine learning to accelerate design cycles and improve predictive accuracy. 
• Develop automated simulation workflows integrating CAD, meshing, solving, and post-processing for scalable and repeatable analysis. 
• Enable data-driven engineering through pipelines for model calibration, surrogate modeling, and rapid design iteration. 

 

4. Cross-Functional Integration 

• Bridge product and process domains ensuring simulation insights translate into actionable design and manufacturing decisions. 

 

5. Validation, Robustness & Governance 

• Lead model validation and correlation integrating lab testing with simulation for high-confidence predictions. 
• Drive robustness and reliability engineering, incorporating variation-aware design, tolerance stack-up, and failure mode consideration 
• Establish best practices and standards for AI agents based on predictive engineering across teams, and product lines. 

What your background should look like:

Required Skills/Experience:

• Bachelor’s degree in Mechanical Engineering or Physics with 8+ years of experience, or a Ma