At EY, youll 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 were 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. 

EY-Consulting Data and Analytics 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 strong 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.

What working at EY offers

At EY, were dedicated to helping our clients, from startups to Fortune 500 companies and the work we do with them is as varied as they are.

You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer:

• Support, coaching and feedback from some of the most engaging colleagues around
• Opportunities to develop new skills and progress your career
• The freedom and flexibility to handle your role in a way thats right for you

EY | Building a better working world 

 
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.  

 
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.  

 
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.