EY GDS Consulting AI and DATA AI Architect Associate Director

EY GDS Associate Director AI Architect

As part of our EY-GDS we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking Insurance Manufacturing Healthcare Retail Manufacturing and Auto Supply Chain and Finance.

The opportunity

Were looking for Associate Director (AI Architects) with strong technology and data understanding having proven pre-sales & delivery capability. This is a fantastic opportunity to be part of a leading consulting firm as well as a part of growing consulting practise.

Your key responsibilities

Business Value Engineering & Consultative Selling

• Partner with Csuite and senior business leaders to understand strategic priorities and identify AI-led transformation opportunities that deliver clear business value.
• Shape articulate build future architecture and present compelling value propositions solution narratives and business cases for AI/GenAI/Agentic AI engagements.
• Drive account teams in pursuit cycles contributing to RFP responses solution design storyline decks and client presentations.
• Lead client discovery and ideation workshops to define AI use cases roadmap and ROI frameworks.
• Drive consultative selling by helping clients understand where AI can meaningfully impact operations customer experience finance and industryspecific value chains.

AI Architecture Design & Solutioning

• Architect endtoend AI Generative AI and Agentic AI solutions across Azure (Azure AI Azure OpenAI) AWS (SageMaker) and GCP (Vertex AI).
• Leverage leading AI platforms such as OpenAI Azure OpenAI Hugging Face LangChain vector databases (Pinecone ChromaDB) and agent orchestration frameworks.
• Design architecture patterns for enterprise AI systemsincluding RAG autonomous agent workflows LLMOps and scalable cloud-native deployments.
• Work with data engineering and data science teams to define data models pipelines and ML development workflows using Databricks Synapse Snowflake Spark Kubernetes Docker etc.

Delivery Oversight & Technical Leadership

• Oversee delivery of AI/GenAI projects to ensure architecture integrity engineering quality and alignment to business value commitments.
• Act as the technical escalation point during delivery guiding solution teams and ensuring adherence to best practices.
• Review detailed solution designs code and architectural artifacts to maintain technical rigor.
• Mentor and coach architects AI engineers and delivery teams on solution design coding standards and engineering excellence.

Innovation Prototyping & Thought Leadership

• Drive the development of POVs accelerators prototypes and demos using Azure AI OpenAI NVIDIA AI and related technologies.
• Create industry-specific and horizontal reference architectures reusable assets and solution frameworks.
• Represent the practice in client discussions internal leadership forums and external industry events on AI strategy and innovation.

Engineering & Build (Selective / Hands-on as Needed)

• Lead by example with handson prototyping when required; write and review high-quality testable code in Python and other languages.
• Guide teams in adopting modern practices for MLOps/LLMOps DevOps observability and secure deployment.

To Qualify for the Role You Must Have

• Extensive presales and consultative experience with the ability to diagnose business problems frame value propositions and connect AI capabilities to measurable business impact.
• 16 years of professional experience including 58 years architecting and deploying enterprisescale AI/ML GenAI and Agentic AI solutions on cloud or onprem environments.
• Experience in working & managing global stakeholders.
• Should have driven significant business outcomes as a part of their role.
• Strong RFP/RFI leadership experience including solution shaping writing technical sections and conducting client-facing architecture and value engineering workshops.
• Deep expertise in designing AI solutions using microservices and cloud-native architectures with strong understanding of Agentic AI AI-ready data and enterprise-scale LLM solution patterns (RAG agents orchestration).
• Bachelors or Masters degree in Computer Science Data Science Engineering or a related technical field.
• Proven experience defining MLOps LLMOps and AgentOps architectures including model lifecycle automation observability governance and responsible AI.
• Hands-on experience deploying AI/ML solutions on Azure AWS and/or GCP with strong understanding of platform-native services (Azure AI Azure OpenAI AWS Bedrock GCP Vertex/Gemini).
• Strong experience using and orchestrating LLMs across cloud platformsOpenAI Azure OpenAI Bedrock Vertex AI Gemini AI vector DBs and agent frameworks.
• Solid background in data modeling SQL and modern data architectures (Databricks Snowflake Synapse).
• Strong foundational understanding of machine learning deep learning NLP and Generative AI.
• Advanced programming skills in Python (and optionally PySpark) for prototyping validation and reference implementations.
• Experience integrating enterprisegrade security identity and authentication into AI/ML and LLM-based applications.
• Proven expertise deploying AI/ML workloads on Kubernetes Web Apps Databricks or similar cloud-native platforms.
• Strong working knowledge of MLOps / LLMOps / AgentOps toolchainsGit MLflow feature stores CI/CD batch inference real-time endpoints.
• Familiarity with Azure DevOps GitHub Actions Jenkins Terraform AWS CloudFormation and related DevOps tooling.
• Working knowledge of Responsible AI principles governance model risk management and compliance.
• Demonstrated experience delivering enterprise-grade production-ready architectures and guiding delivery teams through implementation.
• Strong understanding of data strategy cloud-native engineering analytics modernization and platform-driven transformation.

Ideally Youll Also Have

• Project and client management skills.
• Experience in solutioning and pre-sales engagements.
• Exposure to data mesh principles and domain-oriented data product design.
• Familiarity with data fabric architectures and multi-cloud data strategies.
• Familiarity with real-time analytics

What we look for

People with technical experience and enthusiasm to learn new things in this fast-moving environment

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