GMx-Transformation Architect - AI- Automation -Manager

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Job Description – Transformation Architect – AI / Automation (Manager)

Function: Clients & Industries, EY Global Delivery Services India LLP

As part of EY’s GMx (Global Managed Services Transformation) initiative, we are re imagining how next-generation managed service transformations are designed and delivered—leveraging modern AI, machine learning, deep learning, automation, cloud-native engineering, and intelligent operations to build future-ready, insight-driven service delivery models.

The Opportunity

As part of EY’s GMx (Global Managed Services Transformation) initiative, this role leads AI driven transformation/ modernization across Managed Services. You will lead, architect, and deliver next generation solutions using modern AI (Gen AI, Agentic AI) , machine learning, deep learning, MLOps, automation, with cloud native engineering to transform managed service operations into scalable, cost effective, value driven, insight led, AI enabled service models. This role enables EY to accelerate value, enhance operational outcomes, and build the future ready Managed Services operations.

Your Key Responsibilities
• Lead and architect AI driven transformation initiatives for Managed Services.
• Hold customer discussions to enable the customer with required information and give direction the program.
• Act as tech lead for the AI led managed service transformation programs - taking value driven tech decisions.
• Lead end to end delivery of AI modernization modules under transformation programs (design → build → deploy → ship). Own up part of program management activities.
• Deliver AI/ML-driven transformation across multi year managed services engagements.
• Lead and mentor cross-functional teams (AI engineers, ML engineers, automation developers, data engineers, cloud specialists).
• Define governance, delivery frameworks, KPIs, quality standards, and operational oversight.
• Translate client needs into AI/automation/data use cases, backlogs, and solution roadmaps.
• Identify modernization opportunities using analytics, automation discovery, and process re-engineering.
• Drive continuous improvement using AIOps, observability, predictive insights, and automation-first processes.
• Ensure security, compliance, data protection, and operational stability across all AI and data platforms.