Staff Software Engineer (Mechanical Engineering & Agentic AI)

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 Tyco Electronics Singapore Pte Ltd (TE Connectivity) is looking for a Staff R&D Scientist/Engineer to join our Corporate R&D Center. The Staff Scientist/Engineer will be a senior technical contributor within the Artificial Intelligence team and will help advance the AI Hub for TE in Singapore. The role will lead the development and deployment of AI technologies for engineering, spanning data science, machine learning, generative and agentic AI, simulation, CAD, manufacturing, and data-driven product and process development. The position is based at our Singapore HQ. The Singapore Corporate R&D Center is chartered to work with the CTOs and Advanced Development Groups of TE Business Units to identify technical areas of interest for R&D and develop forward-looking technologies that deliver broad value to the business. As part of TE's Digitalization strategy, this Staff-level role is expected to provide technical leadership, define scalable AI approaches, guide cross-business-unit projects, mentor less-experienced engineers, and translate emerging AI capabilities into practical engineering solutions that improve efficiency, reduce cost, and decrease time to market. Job Responsibilities Provide technical leadership for engineering AI initiatives, helping define technology direction, reusable solution approaches, and project roadmaps for the Singapore AI Hub. Lead multiple strategic, cross-functional projects that apply data science and AI to new product development, product design, manufacturing process development, material formulation, testing, and other engineering workflows. Develop and guide advanced AI/ML solutions using experimental, simulation, CAD, manufacturing, and enterprise engineering data, including surrogate modeling, optimization, inverse design, computer vision, generative design, and other appropriate techniques. Develop agentic AI solutions for engineering use cases, including workflow and multi-agent orchestration, as well as integration with engineering tools and data sources such as CAD/CAE, simulation, PLM and internal knowledge systems. Establish evaluation and validation approaches for existing commercial AI solutions, including model performance, robustness, uncertainty, engineering/physics consistency, safety, guardrails, traceability, and business impact. Work in a multi-disciplinary environment with specialists in data science, mechanical engineering, material science, mechanics, additive manufacturing, software engineering, and other fields. Collaborate with multiple business units to identify high-value opportunities, define requirements and deliverables, make technical trade-offs, and drive projects from problem definition through validation and implementation. Create awareness across TE of the AI modeling and agentic AI…