Sr. Engineering AI Enterprise Architect

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Sr. Engineering AI Enterprise Architect

5/26/26

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

The Engineering AI Enterprise Architect is a senior AI technical authority responsible for the safe, consistent and scalable use of AI across a global engineering organisation.   The role owns the Engineering AI solution design framework, including the architecture principles, reusable patterns, technical standards and production expectations used by business units to design AI models, agents, workflows and solution concepts. It helps identify common AI capabilities, reduce duplication and ensure local solutions are positioned for broader enterprise scale.Working within a wider delivery model, the role provides AI expertise across solution design, model and agent quality, architecture fit, integration quality and technical issue resolution. It requires deep AI solution design expertise, credibility in engineering environments, enterprise architecture awareness and the ability to guide technical contributors without relying on direct authority.The role partners closely with Engineering Systems and Data. The AI Enterprise Architect is accountable for the AI technical framework, solution patterns, model and agent design standards and long-term scalability decisions. The Engineering Systems and Data team are accountable for the systems, data, supplier and integration capabilities required to deliver those AI patterns effectively. Your main tasks:

Define and maintain the engineering AI technical framework, including architecture principles, reusable patterns, readiness criteria, governance checkpoints and lifecycle expectations. Scale AI solutions across business units by assessing local designs, identifying reuse potential, industrialising successful prototypes and guiding solutions toward production ready capability. Create and maintain the engineering AI technology roadmap across tools, agents, models, workflows, data products, integrations and reusable services. Identify common AI capabilities required across multiple use cases, such as retrieval, similarity search, recommendation logic, engineering reasoning, orchestration, evaluation and shared data services. Coordinate architecture alignment across business units, engineering teams, systems leads, subject matter experts, IT, data teams, suppliers and vendors. Review technical proposals and solution designs for scalability, maintainability, security, integration quality,