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    Ernst Young logo

    GMx-Transformation Architect - AI- Automation -Manager

    Ernst Young · Bengaluru · onsite · Posted 44d ago

    Undisclosed8–12 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    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.
    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.
    Technical Expertise Requirements MLOps & AI Platform Engineering (Must)
    • 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.
    Cloud-Native AI Engineering (Must)
    • Strong understanding of CI/CD for ML, model registries, feature stores, drift detection, and model monitoring.
    • Hands-on experience with Azure ML, Databricks, AWS Sagemaker, Vertex AI, or equivalent enterprise AI platforms.
    Data Engineering (Desirable)
    • Familiarity with lakehouses, ETL/ELT, streaming pipelines, and real-time analytics.
    • Experience with Databricks, Spark, and cloud-native data engineering services.
    To Qualify for the Role, You Must Have
    • Ability to lead Transformation programs (multiple modules).
    • 812 years of experience in AI-driven technology delivery; 36+ years in AI/ML leadership roles.
    • Deep expertise in modern AI, ML/DL, MLOps, automation, and cloud-native engineering.
    • Strong Python development background.
    • Experience building, deploying, and shipping large-scale AI products in cloud-native production environments.
    • Experience identifying high-value AI use cases through data-driven value quantification.
    • Proven track record delivering complex AI-driven transformation programs.
    • Strong stakeholder and client management skills.
    • Preferred certifications: Cloud (Azure/AWS/GCP), AI/ML, Technical Architecture for AI/ML.
    Skills and Attributes for Success
    • Strong analytical, conceptual, and problem solving skills.
    • Excellent communication, presentation, and stakeholder engagement abilities.
    • Quality-oriented and detail-focused mindset.
    • Ability to work independently and manage complex multi-disciplinary programs.

    Sourced from naukri

    Skills

    AutomationAws SagemakerAIOpscloud nativedata platformsamazon web servicesAksdata protectionazure mlAnalyticsCapital MarketsDatabricksData EngineeringcloudArchitectureDeep LearningData GovernancecomplianceAi PlatformMicrosoft AzureArtificial Intelligence

    About Ernst & Young

    Ernst Young logo

    Ernst Young

    Management Consulting

    44k+

    employees

    2002

    24 years old

    Gurgaon / Gurugram, Haryana

    India

    ₹15.3L PA avg

    Avg at Ernst & Young

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