Why you join:

Disclaimer: this role is remote, can be based anywhere out of EMEA.

AI is transforming how we deliver engineering excellence and innovation. Effective leadership in this transformation is key to turning potential into lasting, high-value impact.The Transformation Manager plays a pivotal role in driving the execution of AI-enabled initiatives that advance engineering productivity within a specific business segment. Reporting to the Transformation Director, this role is responsible for driving coordinated delivery of multiple AI programs and projects that enhance product development, optimise operations, and enable intelligent automation across the segment.The successful candidate will combine strong technical literacy with proven program management expertise, leading transformation through disciplined execution, stakeholder collaboration, and effective change adoption in complex engineering environments.

Your main tasks:

Program Leadership & Delivery

• Lead end-to-end project management of AI initiatives across engineering functions, from concept through deployment.
• Coordinate multiple interrelated projects, ensuring alignment of scope, schedule, and resources to deliver on project objectives.
• Partner with the Segment Transformation Director, IT organisation, and business stakeholders to ensure AI initiatives align segment and enterprise goals.
• Manage execution rhythm, track progress, and proactively resolve issues to keep projects on schedule.

Stakeholder Coordination & Communication

• Collaborate with engineers, IT, domain experts and data scientists, to define program scope, objectives, and success metrics.
• Ensure clear, consistent communication across technical and business teams throughout the program lifecycle.
• Deliver concise executive-level updates on progress, risks, and business value outcomes.

Governance & Standards

• Develop and apply Engineering AI standardised delivery frameworks, templates, and KPIs within the segment.
• Ensure compliance with TE’s data governance, cybersecurity, and ethical AI standards.
• Support audit readiness and adherence to approved processes and governance gates.

Change Management & Adoption Enablement

• Embed change management practices into delivery plans to drive adoption of AI tools and solutions.
• Develop rollout strategies, communications, and training in partnership with the Segment Transformation Director and continuous improvement Leaders.
• Monitor adoption metrics and feedback, ensuring sustained behavioural and process change.

Performance Management & Continuous Improvement

• Develop and manage detailed program plans, budgets, and resource allocations.
• Track KPIs, business outcomes, and value realization against approved business cases.
• Capture lessons learned and best practices for repeatability and scalability.

Your ideal profile:

• Preferred Bachelor’s degree in Engineering, Computer Science, or related field pr equivalent professional experience
• PMP/Prince 2, Program Management, or Agile certification preferred.
• 10+ years of program or portfolio management experience in engineering, AI, or digital transformation.
• Proven success leading large, cross-functional programs across global teams.
• Familiarity with engineering systems (CAD/CAE/PLM/Simulation).
• Experience with AI/ML technologies an advantage.
• Experience embedding change management and adoption practices in technical programs.

Skills:

• Excellent leadership, organisation, and multitasking abilities across concurrent projects.
• Driving results through influence and partnership
• Strong analytical and decision-making skills; ability to communicate effectively at executive and technical levels.
• Skilled in stakeholder alignment, risk management, and executive reporting.
• Understanding of AI/ML deployment, data integration, and digital engineering workflows an advantage.

Succes in this role:

• Be results focused
• Deliver AI initiatives on time, within scope, and aligned to TE Engineering’s enterprise AI framework.
• Enable measurable productivity gains and engineering efficiency improvements.
• Strengthen cross-functional collaboration between business, IT, and leadership.
• Drive adoption and sustainable use of AI solutions through effective change management.
• Establish consistent, scalable execution practices that accelerate Engineering transformation across segments.

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Competencies