EY seeks a dynamic Associate Director to spearhead the architecture, engineering, and operational advancements of enterprise-scale AI platforms. This role is pivotal in driving intelligent operations and enhancing digital employee experiences by overseeing the entire lifecycle from build to continuous improvement.

This position demands profound expertise in Agentic AI, Generative AI, enterprise application architecture, data platforms, automation, observability, and AI operations. The chosen candidate will define the enterprise architecture strategy for AI-powered platforms, design robust and scalable solutions, and ensure the successful integration and operation of AI capabilities across the organization.

Success hinges on a demonstrated capacity to architect, build, and manage secure, resilient, and highly available enterprise products at scale, while championing innovation and fostering widespread adoption of AI-driven solutions. The role offers the opportunity to transform emerging AI technologies into production-ready solutions that deliver tangible business value, working collaboratively across various business, engineering, architecture, and operations teams.

Lead the end-to-end architecture vision, standards, and technical strategy for enterprise AI and Agentic AI solutions. Design single- and multi-agent architectures, including orchestration, reasoning, memory, and human-in-the-loop controls. Architect AI-driven operational capabilities for issue observation, diagnosis, prediction, prevention, and resolution.

Develop intelligent conversational experiences that understand user context and initiate actions safely. Architect enterprise knowledge and intelligence platforms using structured/unstructured data, RAG, and knowledge graphs. Define Generative AI architecture encompassing model strategy, grounding, evaluation, and guardrails.

Architect scalable enterprise applications using microservices, APIs, and cloud-native patterns. Establish reusable integration patterns across diverse systems. Define architecture standards for security, privacy, Responsible AI, and governance. Establish engineering standards for scalability, availability, and performance.

Lead architecture governance, technology evaluations, and build-versus-buy decisions. Provide technical leadership and mentorship to architecture, engineering, and platform teams throughout the product lifecycle. Ensure AI services meet stringent availability, reliability, and performance objectives.

Establish end-to-end observability across applications, infrastructure, and AI models. Drive incident and problem management, focusing on root-cause analysis and prevention. Implement AIOps, LLMOps, and AgentOps practices for quality, performance, and cost optimization.

Utilize operational insights for continuous platform improvement. Engage and influence senior technology and business stakeholders to align AI platform strategy with enterprise objectives. Lead and mentor high-performing teams, fostering capability-building across functions.

Possess deep expertise in enterprise architecture, modern application engineering, and AI platform design. Demonstrate strong understanding of Agentic AI, Generative AI, multi-agent systems, orchestration frameworks, and AI evaluation methodologies. Proven ability to architect and operate large-scale, highly available, and resilient enterprise platforms.

Expertise in enterprise application architecture, distributed systems, APIs, event-driven architectures, and cloud-native engineering. Strong understanding of enterprise knowledge platforms, RAG, semantic retrieval, and knowledge graph architectures. Experience establishing observability, reliability engineering, AIOps, LLMOps, and AgentOps practices.

Solid grasp of enterprise security, identity management, privacy, governance, and Responsible AI principles. Exceptional problem-solving and systems-thinking capabilities, balancing innovation with governance and operational excellence. Strong communication, stakeholder management, and executive engagement skills.

Demonstrated ability to influence technical direction, lead complex initiatives, and mentor engineering teams. Ability to drive solutions from concept through architecture, engineering, deployment, operations, and continuous improvement. Experience with .NET/C# and enterprise application architecture is desirable. Experience with agent orchestration platforms and enterprise AI development platforms is a plus.