Senior Domain Architect AI - EY Fabric Post-Sales

About the role

EY is looking for a Senior Domain Architect for its Fabric AI post-sales organization. The architect defines repeatable AI and GenAI architecture patterns so that AI Factory, OpenAI-related capabilities, GenAI integrations, model orchestration, evaluation, monitoring and operational controls are delivered through reusable, governed patterns rather than bespoke implementations. The role focuses on post-sales adoption, architectural integrity and repeatability.

Key responsibilities

• Define EY Fabric AI reference architectures covering AI Factory, OpenAI integrations, GenAI workloads, model orchestration, agentic patterns, retrieval-based approaches, deployment, evaluation, monitoring and lifecycle management.
• Create repeatable AI design patterns for scenarios such as GenAI application onboarding, secure model access, prompt orchestration, RAG-style patterns, evaluation workflows, telemetry and operational controls.
• Develop AI accelerators including architecture blueprints, starter kits, integration templates, deployment patterns, evaluation frameworks, monitoring patterns, reusable prompts, configuration guidance and handoff packs.
• Define guardrails for responsible AI delivery, including access controls, data boundaries, auditability, monitoring, human oversight and operational risk management.
• Partner with AI Product, Engineering, Security, Risk and Reliability teams to align patterns with platform roadmap and governance.
• Act as escalation point for complex AI architecture questions and turn recurring challenges into reusable patterns and playbooks.
• Maintain AI architecture assets in EY Fabric knowledge repositories such as GitHub, SharePoint and Teams, and measure effectiveness through pattern adoption and reduced bespoke builds.
• Mentor mid-level AI Architects and review patterns, accelerators and handoff artifacts for quality and consistency.

Required profile

• Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence or equivalent experience.
• 10+ years of engineering experience with recent GenAI architecture experience, including significant AI, ML, GenAI or platform delivery work.
• Experience building reusable AI patterns, accelerators, technical standards or implementation playbooks.
• AI, cloud architecture, security or data certifications preferred.

Required skills

• Designing and governing production AI, ML or GenAI systems.
• Familiarity with AI Factory, OpenAI-style integrations, model orchestration, RAG patterns, evaluation, monitoring and lifecycle management.
• Cloud architecture fundamentals including identity, networking, security, logging and observability.
• Responsible AI, data governance, security, risk and operational controls.
• Creating reusable AI architecture assets, templates and implementation guides.