Client Technology - Architecture - Lead Software & AI Architect

Client Technology - Architecture - Lead Software & AI Architect

At EY, we’re shaping the future with confidence and confidence. Join EY to build a better working world, fuel innovation, and drive AI transformation.

EY Client Technology seeks a Lead Architecture Architect to design scalable, cloud‑native, agentic AI systems for business‑critical global products. The role blends strategic vision, hands‑on implementation, and collaboration across engineering, product, AI safety, and operations.

• Build relationships with business partners to translate strategy into architecture blueprints and product roadmaps, including agentic AI solutions.
• Own the technology, architecture, and design landscape from solutioning to adoption, with deep expertise in distributed systems, containerization, orchestration, agent frameworks, and security patterns.
• Design and implement enterprise‑scale distributed and agentic AI solutions using modern protocols (REST, Graph
  
  QL, MCP, A2A), Kubernetes, event‑driven architecture, OAuth 2.0/OpenID Connect, and guardrails (NeMo Guardrails, Guardrails AI).
• Lead engineering teams, set technology direction, act as the critical glue among Engineering, Product, AI Safety, and Operations, and drive end‑to‑end delivery.
• Conduct technical feasibility assessments, vendor evaluations, proof of concepts, and present solution options to business stakeholders.
• Collaborate with AI engineers, prompt engineers, AI safety specialists, data scientists, platform teams, and infosec to deliver compliant, secure, AI‑governed architectures.
• Provide leadership in reusable component libraries, containerized services, agent templates, reasoning patterns, and observability via Open Telemetry.
• Coach, mentor, and support development teams, ensuring artifact quality, security standards, and AI safety compliance through code reviews, prompt reviews, and architecture validation.
• Operate as the architecture elevator, connecting boardroom strategy with server room implementation across distributed global teams.

• Led global engineering teams and architects, driving large, complex portfolios and embedding enterprise‑wide architecture governance.
• Expert proficiency in C#, Java, JavaScript, Type Script, or Python, with a proven record of designing enterprise‑scale AI‑powered systems.
• Hands‑on experience with web APIs (REST, Graph
  
  QL), containerization (Docker, Kubernetes), event‑driven patterns, OAuth 2.0/OpenID Connect, MCP, and A2A communication frameworks.
• Architecture leadership skills with advanced understanding of modern architecture patterns and proven execution on large‑scale implementations.
• Deep experience in application integration, cloud infrastructure architecture, data pipelines, security, and delivery of functional and non‑functional platform capabilities.
• Comprehensive knowledge of containerization, orchestration, event‑driven systems, message queuing, and enterprise security patterns.
• Strong background in security best practices, enterprise compliance, and regulatory standards in enterprise environments.

• 2+ years of hands‑on experience architecting enterprise‑scale agentic AI systems, including multi‑agent orchestration platforms serving significant user bases.
• Major agent frameworks:
  Lang Chain/Lang Graph, Microsoft Auto Gen, Semantic Kernel, and Microsoft Agent Framework (at least two frameworks in production).
• Expertise in agent communication protocols: MCP, A2A, AG‑UI, OpenAPI, JSON‑RPC, SSE, Web Sockets.
• Advanced reasoning techniques:
  ReAct, CoT, ToT, planning patterns, and multi‑plan selection.
• Experience with NeMo Guardrails, Guardrails AI, Azure AI Content Safety, and multi‑layer guardrails implementation.
• Proficiency in LLM evaluation frameworks (Deep Eval, RAGAS, Lang Smith) and observability for multi‑agent systems.
• Expert‑level skills in RAG, Agentic RAG, Graph
  
  RAG, Multi‑Modal RAG, and two or more vector databases.
• Strong background in event‑driven architectures, data streaming, real‑time processing, and microservices platforms.

• Bachelor’s or Master’s Degree in Engineering, Computer Science, Data Science, AI/ML, or…