Staff Software Engineer (Mechanical Engineering & Agentic AI)

TE Connectivity Corporate Office Singapore; Santo Niño 1st; On-site; PHP 6,890,000 - 10,335,000; Full time

Job summary

TE Connectivity Singapore is seeking a Staff R&D Scientist/Engineer to join our Corporate R&D Center. You will lead AI initiatives across data science, ML, and CAD-driven engineering to advance the AI Hub for TE.

Based at our Singapore HQ, you will mentor engineers, guide projects from problem definition to deployment, and collaborate with business units and external partners to deliver practical AI solutions that reduce cost and time to market.

Qualifications

• PhD with 4+ years, or Master with 7+ years, or Bachelor with 10+ years in related field.
• Proven track record leading technically complex R&D or engineering AI projects and delivering measurable impact.
• Deep understanding of data science and artificial intelligence, including machine learning model development, validation, and optimization.
• Hands‑on knowledge of generative AI and agentic AI concepts and technologies, such as LLMs, RAG, embeddings, tool calling, orchestration.
• Broad understanding of multiphysics simulation (FEA) with CAD/CAE workflows; experience with AI-assisted design is desirable.
• Strong programming skills in Python and ML frameworks; experience with software development practices.
• Broad knowledge of manufacturing processes, materials, and product design.
• Strong leadership and stakeholder management across functions and distributed teams.
• Excellent communication to explain AI concepts and risks to engineers and senior stakeholders.

Responsibilities

• Provide technical leadership for engineering AI initiatives, defining technology direction and roadmaps for the Singapore AI Hub.
• Lead multiple cross‑functional projects applying data science and AI to new product development, design, and manufacturing workflows.
• Develop AI/ML solutions using surrogate modeling, optimization, design tools, and data sources.
• Develop agentic AI workflows and integration with CAD/CAE, simulation, PLM, and enterprise systems.
• Establish evaluation approaches for model performance, robustness, safety, and business impact.
• Collaborate with data science, mechanical engineering, materials, software, and other teams across TE sites.

Skills

Generative AI

Agentic AI

Python

Data science

Machine learning

Leadership

Cross-functional collaboration

Multiphysics simulation

Education

PhD in related field

Master's degree

Bachelor's degree

Tools

CAD/CAE tools

AI deployment

MLOps/LLMOps

Job description

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.

Duties & 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 capabilities of the Singapore center and support adoption of reusable methods and best practices across engineering teams.

• Work with local and global TE sites, external customers, technology partners, and research institutes to address urgent or strategic needs, develop advanced AI techniques, validate results, and enable effective knowledge transfer.

Qualifications:

Required:

• Advanced degree in Mechanical Engineering, Computational Engineering, Applied Mechanics, Data Science, Artificial Intelligence, or a closely related field. Typically, PhD with 4+ years, Master degree with 7+ years, or Bachelor degree with 10+ years of relevant industrial/research experience.

• Demonstrated track record of independently leading technically complex R&D or engineering AI projects and delivering measurable impact in product development, simulation, manufacturing, materials, or related engineering domains.

• Deep understanding of data science and artificial intelligence, including machine learning model development, feature/data engineering, validation, optimization, and the ability to select appropriate algorithms and architectures for engineering problems.

• Hands‑on knowledge of generative AI and agentic AI concepts and technologies, such as large language models (LLMs), RAG, embeddings/vector search, tool/function calling, agent orchestration and secure integration with enterprise or engineering systems.

• Broad understanding of multiphysics simulation such as finite element analysis, together with practical experience in CAD and engineering design workflows; experience with generative or AI‑assisted design is highly desirable.

• Strong programming skills in Python or similar languages and hands‑on experience with commonly used data science/ML frameworks and software development practices.

• Broad knowledge of manufacturing processes, material behavior, product design, and the relationship between physical engineering constraints and data‑driven/AI models.

• Strong project leadership and stakeholder management skills, with experience working across functions, business units, and geographically distributed teams.

• Strong communication skills with the ability to explain complex AI concepts, technical risks, and recommendations to both engineering specialists and senior stakeholders.

Preferred:

• Familiarity with TE products (connectors, cables, sensors, etc.) and manufacturing processes such as molding, extrusion, plating, stamping, and assembly.

• Experience integrating AI with engineering software or enterprise systems, including CAD/CAE tools, simulation platforms, APIs, databases, cloud or on‑premise AI platforms, and containerized deployment.

• Experience with MLOps/LLMOps, model and agent evaluation frameworks, data governance, security, and enterprise deployment of AI solutions.

• Track record of technical publications, patents/invention disclosures, externally funded research, or collaboration with universities/research institutes.

• Familiarity with project management and software collaboration tools.

Competencies:

• Values: Integrity, Accountability, Teamwork, Innovation

• Technical Leadership and Mentoring

• Strategic Thinking and Technology Foresight

• Collaboration, Communication, and Influence

• Strong Interpersonal Skills

• Action Oriented

• Adaptability/Flexibility

• Creativity/Innovation

• Dealing with Ambiguity

• Problem Solving/Analysis

• Technical Depth and Engineering Judgment

• Continuous Learning