Sr. Engineering AI Enterprise Architect

Overview

As Engineering AI Enterprise Architect, you will set the AI technical framework and patterns across TE’s global engineering teams. You’ll drive scalable, secure AI adoption by defining architecture principles, reusable patterns and governance checkpoints. You will guide solution designs toward production readiness while coordinating with engineering, data, IT and vendor partners. This role offers impact at scale, shaping how AI capabilities integrate with engineering processes and enterprise systems.

Pay / Benefits

• Competitive salary package
• Performance-based bonus plans
• Health and wellness incentives
• Employee stock purchase program
• Community outreach programs / charity events
• Employee resource Group

Responsibilities

• 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 prototypes and guiding production-ready solutions
• 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 use cases (retrieval, similarity search, recommendation logic, engineering reasoning, orchestration, shared data services)
• Coordinate architecture alignment across business units, engineering teams, systems leads, SMEs, IT, data teams, suppliers and vendors
• Review proposals and designs for scalability, maintainability, security, integration quality, reuse potential and enterprise fit
• Embed security, data, IP protection, responsible AI, testing, documentation, monitoring and support into delivery standards
• Reduce duplicate development by steering teams toward shared platforms, common services and standard architecture patterns

Key requirements

• Proven track record designing and scaling AI-enabled solutions in complex operational environments
• Experience as a senior AI technical authority defining standards and driving reuse
• Experience taking GenAI, agentic AI, RAG or AI workflow solutions from concept to production with measurable impact
• Strong background in enterprise or solution architecture linking AI to business processes and systems
• Ability to engage credibly with engineering leaders, architects, IT, data teams and vendors
• Experience creating technical frameworks, reference architectures or reusable patterns
• Success in global, matrixed organisations driving alignment without direct authority

• Credible communication with diverse stakeholders
• Systems thinking
• Disciplined architecture and governance
• LLM/GenAI design, prompt/context design, grounding, tool use, scalability trade-offs
• Agentic AI, orchestration and human-in-the-loop patterns
• Classical ML/DS lifecycle: supervision, unsupervised learning, feature engineering, deployment patterns

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