Senior Domain Architect AI

Position Summary

You are a strategic Architect within the EY Fabric post-sales organization accountable for defining repeatable AI and GenAI architecture patterns that enable EY Fabric adoption at scale. Your role is to ensure AI Factory OpenAI-related capabilities GenAI integrations model orchestration evaluation monitoring and operational controls are delivered through reusable governed and easy-to-consume patterns rather than bespoke implementations.

This role is focused on post-sales adoption architectural integrity and repeatability. You will create the reference architectures accelerators guardrails and implementation blueprints that help Forward Deployed Engineers and delivery teams implement AI solutions consistently while managing risk cost security and operational readiness.

Essential Functions of the Job

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 common post-sales scenarios such as GenAI application onboarding secure model access prompt orchestration RAG-style solution 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
Ensure AI accelerators are easy to consume by Forward Deployed Engineers delivery teams and segment-aligned teams
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 post-sales patterns with platform roadmap and governance expectations
Act as the senior escalation point for complex AI architecture questions that go beyond standard implementation playbooks
Convert recurring AI implementation challenges into reusable patterns playbooks and accelerators
Define clear handoff expectations between Presales Domain Architecture Forward Deployed Engineering and ongoing support teams
Govern exceptions to standard AI patterns and determine whether new supported patterns are required
Maintain AI architecture assets in agreed EY Fabric knowledge repositories such as GitHub SharePoint Teams and internal knowledge hubs
Measure AI architecture effectiveness through pattern adoption reduction in bespoke builds implementation speed operational quality and reuse of accelerators
Mentor mid-level AI Architects and help build post-sales AI architecture maturity across EY Fabric
Analytical and Decision-Making Responsibilities

Evaluate AI solution designs for scalability security privacy cost reliability observability and operational readiness
Decide when an AI use case should follow an existing standard pattern versus requiring a new architecture pattern
Prioritize AI accelerator development based on recurring demand risk profile delivery complexity and adoption impact
Identify common sources of AI delivery friction and drive platform-level or pattern-level improvements
Assess whether AI implementations are aligned to EY Fabric guardrails and responsible AI expectations
Knowledge and Skills Required

Strong experience designing and governing production AI ML or GenAI systems
Familiarity with AI Factory concepts OpenAI-style integrations model orchestration RAG patterns evaluation monitoring and lifecycle management
Strong cloud architecture fundamentals including identity networking security logging and observability
Understanding of responsible AI data governance security risk and operational controls
Experience creating reusable AI architecture assets templates implementation guides or accelerators
Ability to communicate AI architecture decisions tradeoffs and risks to technical and executive stakeholders
Strong ability to work across Product Engineering Security Risk Growth and delivery teams
Supervision Responsibilities

Provide technical leadership to AI Architects and senior engineers
Review AI patterns accelerators and handoff artifacts for quality and consistency
Coach teams on using approved EY Fabric AI patterns instead of bespoke implementations
Job Requirements

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