Job Overview

The pace of innovation in artificial intelligence and machine learning continues to accelerate, and the Data and Devices Business Unit is at the center of this transformation. Our customers are building intelligent systems that redefine how data is processed, analyzed, and used across compute, networking, and cloud infrastructure. At TE Connectivity, we support this evolution by delivering scalable, high-quality software solutions that enable next-generation products.

We are seeking a Senior Manager, AI/ML Software Engineering, to lead the strategy, development, and deployment of AI/ML software capabilities that support next-generation products and internal engineering transformation. This leader will build and develop a high-performing organization, drive execution across multiple programs, and partner closely with engineering, product, digital, and business leaders to translate strategic priorities into measurable outcomes.

This role requires a balance of strong technical leadership, organizational leadership, and business acumen. The successful candidate will shape the AI/ML software roadmap, oversee delivery across multiple workstreams, and ensure solutions are scalable, reliable, and aligned with business objectives.

 
What you will be doing…
As a Senior Manager, AI/ML Software Engineering, you will lead a multidisciplinary organization responsible for AI/ML software development, data-driven engineering tools, and scalable platform capabilities that support the Data and Devices Business Unit. You will define operational strategy, develop organizational capability, and drive execution across a portfolio of AI/ML initiatives with impact across multiple functions.

Job Requirements

Strategic Leadership and Organizational Impact

• Define and drive the AI/ML software engineering strategy in support of business and engineering priorities.
• Translate business needs into an actionable portfolio of AI/ML, software, and digital engineering initiatives.
• Lead a complex organization with multiple sub-functions or workstreams, ensuring alignment to medium and long term business objectives.
• Provide leadership on investments, priorities, and tradeoffs to maximize business impact, technical scalability, and operational efficiency.
• Partner with senior leadership to shape roadmaps, operating models, and capability plans for AI-enabled engineering.

Team Leadership and Organizational Development

• Build, lead, and develop a high-performing engineering organization, including managers, technical leaders, and individual contributors.
• Establish clear goals, work plans, resourcing models, and performance expectations across the organization.
• Drive talent planning, succession planning, coaching, and capability development to strengthen organizational depth.
• Foster a culture of accountability, technical excellence, collaboration, and continuous improvement.
• Lead organizational design and staffing decisions in support of business strategy and evolving technology needs.

AI/ML Software Delivery and Execution

• Oversee the development and deployment of AI/ML software, data pipelines, tools, and platforms used in product development, design optimization, and engineering productivity.
• Ensure solutions are scalable, secure, maintainable, and integrated into enterprise and engineering workflows.
• Drive execution across multiple concurrent programs, balancing innovation with operational discipline and delivery rigor.
• Establish best practices for software development, model lifecycle management, validation, and production deployment.
• Monitor execution performance, risks, dependencies, and quality metrics across programs and teams.

Cross Functional and Executive Collaboration

• Partner with software, hardware, systems, product, manufacturing, and business teams to identify high value AI/ML use cases and drive adoption.
• Influence stakeholders across functions and levels, including senior management and executives, to align on priorities and outcomes.
• Communicate strategy, progress, risks, and business value clearly to technical and non-technical audiences.
• Represent the function in key reviews, planning discussions, and external engagements with customers, partners, and vendors as needed.

Operational Excellence, Governance, and Financial Accountability

• Own planning for budget, staffing, and expense priorities across the function.
• Establish operating mechanisms, governance processes, and performance metrics to ensure execution discipline and strategic alignment.
• Assess organizational, technical, and compliance risks across the area of accountability.
• Ensure adherence to schedules, budgets, quality expectations, and company policies.
• Drive continuous improvement in methods, tools, and processes to enhance delivery effectiveness and engineering value.

What your background should look like

• Bachelor’s degree and 13+ years of experience, or Master’s degree and 10+ years of experience, in Computer Science, Software Engineering, Data Science, or a related technical field
• Typically 5+ years of progressive people leadership experience, including leading managers, senior technical professionals, or multiple teams.
• Strong experience leading software engineering, AI/ML, data platform, or digital engineering teams in complex product or technology environments.
• Demonstrated success defining strategy and delivering large-scale, cross-functional programs with measurable business impact.
• Strong understanding of AI/ML technologies, software architecture, cloud or data platforms, and production deployment practices.
• Experience managing budgets, resource planning, and organizational priorities across multiple initiatives.
• Proven ability to influence senior leaders and drive alignment across technical and business stakeholders.
• Strong business acumen with an understanding of how AI/ML capabilities can improve engineering productivity, product performance, and operational outcomes.
• Excellent communication, presentation, and stakeholder management skills.
• Ability to travel 10% to 25% to customers, conferences, partner locations, and TE development sites.

Competencies