GMx-Transformation Architect - AI- Automation -Senior Manager

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Job Description – Transformation Architect – AI / Automation (Senior 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, program manage, 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

Program manage 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 TPM for the AI led managed service transformation programs - taking value driven tech decisions. Lead end to end delivery of AI modernization programs (design → build → deploy → ship). 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.

Technical Expertise Requirements Use Cases & Architecture (Must)

Ability to quickly understand new business processes and identify high ROI AI/ML transformation opportunities. Hands-on experience in architecting (technical + solution architecture) AI/ML-driven transformation assets and platforms. Expertise in embedding security, responsible/ethical AI, and data governance into AI architectures while ensuring clear RoI and value realization.

Modern AI & Agentic AI (Must)

Hands-on experience with LLMs, GenAI, and Agentic AI systems deployed in production on cloud using cloud native capabilities. Expertise in multi-agent orchestration, tool-use agents, workflow agents, and enterprise-safe agentic architectures. Experience with vector databases, embeddings, RAG pipelines, and AI orchestration frameworks.

Machine Learning & Deep Learning (Must)

Strong grounding in supervised/unsupervised ML, tree-based models, forecasting, and statistical modeling. Experience with CNNs, RNNs/LSTMs, Transformers, and generative models. Proficiency in sklearn, MLlib, PyTorch, TensorFlow, or equivalent frameworks. Ability to build, optimize, validate, and deploy ML/DL models at enterprise scale.

MLOps & AI Platform Engineering (Must)

Strong understanding of CI/CD for ML, model registries, feature