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EY-Consulting Data and Analytics Manager / Senior Manager AI/ML Architect

EY's Consulting Services is a unique, industry-focused business unit that provides a broad range of integrated services that leverage deep industry experience with robust functional and technical capabilities and product knowledge. EYs financial services practice provides integrated Consulting services to financial institutions and other capital markets participants, including commercial banks, retail banks, investment banks, broker-dealers & asset management firms, and insurance firms from leading Fortune 500 Companies. Within EYs Consulting Practice, Data and Analytics team solves big, complex issues and capitalize on opportunities to deliver better working outcomes that help expand and safeguard the businesses, now and in the future. This way we help create a compelling business case for embedding the right analytical practice at the heart of clients decision-making.

The opportunity

We are looking for an experienced AI/ML Architect with 12+ years of overall experience in AI/ML, Generative AI, Agentic AI, data science, analytics, cloud, and enterprise technology delivery.

The candidate should have deep expertise in architecting and productionizing enterprise AI solutions, with primary focus on AI/ML, Deep Learning, Generative AI, LLM-based applications, Agentic AI workflows,



and RAG-based architectures.

The role requires supporting knowledge of data platforms, data engineering, data quality, governance, and enterprise data integration, preferably with experience in the insurance and/or financial services domain.

Your key responsibilities

- Lead architecture and solution design for enterprise AI/ML, Generative AI, and Agentic AI initiatives.
- Design end-to-end AI solution blueprints covering problem framing, data requirements, model selection, architecture patterns, integration, deployment, monitoring, and support.
- Understand enterprise data landscapes including data warehouses, data lakes, Lakehouse platforms, operational data stores, data pipelines, metadata, data quality, lineage, governance, and data consumption patterns.
- Collaborate with data engineering teams to ensure AI solutions are supported by reliable data pipelines, governed data access, metadata, data quality checks, and scalable data platforms.
- Guide teams on integrating AI capabilities into modern data platforms such as Snowflake, Databricks, Microsoft Fabric, Azure Synapse, Spark-based platforms, and cloud-native data ecosystems.
- Define reusable AI architecture patterns, solution accelerators, implementation templates, and reference architectures.
- Evaluate and recommend suitable AI/ML,



GenAI, Agentic AI, cloud AI, vector search, and data platform technologies.
- Define responsible AI controls including privacy, security, access control, explainability, auditability, hallucination mitigation, traceability, bias monitoring, and compliance.
- Lead POCs, MVPs, pilots, and production implementations for AI-driven use cases.

Skills and attributes for success

- Strong understanding of AI/ML, deep learning, Generative AI, LLMs, RAG, Agentic AI, model lifecycle, evaluation, monitoring, and productionization.
- Ability to architect enterprise AI solutions that are scalable, secure, governed, explainable, observable, and production ready.
- Working knowledge of modern AI platforms and frameworks such as Azure OpenAI, Azure AI Foundry, Google Vertex AI, Gemini, AWS Bedrock, LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, TensorFlow, PyTorch, and Scikit-learn.
- Good understanding of data engineering and data architecture, including ETL/ELT, data pipelines, warehouses, lakes, Lakehouse platforms, metadata, lineage, data quality, governance, and consumption patterns.
- Exposure to modern data platforms such as Snowflake, Databricks, Microsoft Fabric, Azure Synapse, Spark/PySpark, Hive, or equivalent platforms
- Strong hands-on knowledge of Python and SQL.
- Good understanding of insurance and/or financial services domains, including data sensitivity, regulatory expectations, risk controls, operational workflows, and enterprise technology environments.
- Strong communication, consulting, documentation, stakeholder management, and architecture leadership skills.

📌 EY - GDS Consulting - AI And DATA -AI Architect -Senior manager (Bengaluru)
🏢 EY
📍 Bengaluru