Join EY's Global Managed Services team as a Data & AI Managed Services Solution Architect, Manager. You will play a pivotal role in shaping and articulating innovative managed services for enterprise data platforms, ensuring resilience, trustworthiness, and cost-efficiency. This role is crucial for enabling AI, ML, and agent-based solutions to operate reliably at scale. You'll be instrumental in designing solutions that are not only technically sound but also commercially compelling and aligned with responsible AI and data governance principles.

This is an opportunity to contribute to EY's accelerated growth in managed services, working with a global network of professionals to deliver enhanced value to clients. You'll collaborate with diverse teams to translate complex capabilities into client-ready narratives and measurable outcomes.

As a Data & AI Managed Services Solution Architect, you will lead the development of data & AI solution strategies and compelling narratives, translating client priorities and data maturity into clear solution storylines. You will design end-to-end Data & AI managed services, encompassing platform operations, data management, insights, and AI/ML/agent operations, ensuring platform availability, pipeline resilience, and observability. Your role will involve articulating these solutions through proposals, presentations, and client engagements, and partnering with sales and account leadership. You will also contribute to estimation and commercial input, translating service design into viable staffing, location, and productivity assumptions, working closely with pricing teams to align commercials with service tiers and outcomes.

We are seeking a Manager with over 10 years of experience in Data & AI, technology managed services, data platform operations, analytics application management, or AI operations. A strong understanding of the managed services lifecycle, from pursuit to continuous improvement, is essential. You should possess deep knowledge of major data and AI ecosystems like Databricks, Snowflake, and Microsoft Azure, along with experience in reusable assets or automation for operational productivity and observability. Familiarity with managed services pricing, cloud/platform cost drivers, and FinOps considerations is required. Relevant architecture, cloud, data, AI, service management (e.g., ITIL), or FinOps certifications are highly desirable.