EY is seeking an experienced Engineering Lead – AI to drive the hands-on delivery of enterprise AI, ML, and Generative AI solutions. This player-coach role involves setting engineering standards, coaching teams, and ensuring the production-grade quality, scalability, reliability, and supportability of AI systems. The ideal candidate will possess extensive software engineering experience, deep technical expertise across full-stack and cloud-native architectures, and a proven track record in delivering robust AI-first architectures and data foundations.

Success in this position is measured by the quality and operability of AI systems in production. You will be instrumental in translating the enterprise's AI ambition into tangible, reliable, and scalable systems.

Take end-to-end ownership of AI and GenAI solution delivery, from design through production and ongoing support. Serve as the technical authority for the build team, ensuring high standards for code quality, security, privacy, and compliance. Make critical engineering trade-offs to balance latency, accuracy, cost, reliability, and scale. Own production systems post-launch, managing incident analysis, performance tuning, and architectural evolution.

Collaborate on design and build production-grade GenAI systems, including RAG pipelines, agentic workflows, and prompt integration layers. Work directly with AI Engineers and Data Scientists to productionize models, implement evaluation and monitoring, and optimize inference costs. Define and enforce reference architectures and engineering standards for AI/GenAI systems, driving consistent adoption of clean architecture patterns, CI/CD, and DevOps practices.

Build and evolve AI platforms for model lifecycle management and MLOps/LLMOps. Lead and develop a team of senior engineers, coaching them in backend engineering, GenAI design, and writing production-quality code. Foster a strong engineering culture focused on ownership, rigor, and continuous improvement. Partner closely with AI/ML, Data Science, platform, security, and operations teams, acting as a senior technical voice in governance forums.

A degree in Computer Science/Engineering or equivalent work experience is required. Possess over 10 years of global IT experience, with at least 3 years in global delivery/transformation and 3 years in global operations. Strong hands-on experience in backend languages like Python, Java, or C#, coupled with proven experience in building API-driven, cloud-native systems and a solid understanding of distributed systems, scalability, and reliability patterns.

Essential GenAI/AI engineering experience includes building LLM-powered applications with RAG pipelines, agentic workflows, and prompt orchestration. Familiarity with vector databases, LLM evaluation, observability, guardrails, safety, and cost controls is crucial. Experience operationalizing AI models at scale in enterprise environments is expected.

Additional requirements include strong communication, stakeholder management, influence, leadership, conflict resolution capabilities, and experience leading virtual teams. Familiarity with Python practices, MS Power Platform, ServiceNow, Azure AI Services, and Azure Data Services are considered advantageous.