Location: Dublin 2
Other locations: Primary Location Only
Requisition ID: 1726063
At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.
Join EY and help to build a better working world.
Your Key Client Responsibilities:
This is your chance to lead the future of AI at EY Ireland for Financial Services. As a hands-on architecture & engineering lead, you will design enterprise-grade AI solutions (Agentic & Gen-AI). You will work with cutting-edge technologies and collaborate across diverse teams to deliver impactful, scalable AI systems. This role offers the opportunity to design AI strategy and build solutions that align with global standards and regulatory frameworks for Financial Services.
This role blends deep hands‑on engineering, consulting judgment, and client‑facing delivery ownership. You will carry solutions from concept through production and enable clients to sustainably operate and evolve their AI capabilities.
- Strategy & POV: Shape technical policies and architecture for AI and autonomous systems to strengthen competitive advantage.
- Client Consulting: Lead executive workshops to identify high-value AI use cases, assess readiness, and create ethical adoption roadmaps. Collaborate with stakeholders to align architecture with strategy.
- Solution Structuring: Turn business challenges into actionable technical plans compliant with data governance and security standards.
- Pre-Sales: Act as subject matter expert, supporting sales teams in structuring and estimating complex AI projects.
- Practice Enablement: Integrate AI practice across competencies by leading training and platform expertise development.
- Agent Design: Architect multi-step autonomous agent systems using LLMs, vector databases, and orchestration frameworks with a focus on scale and reliability.
- Architecture Governance: Set technical standards and QA processes for AI and MLOps workflows.
- Tooling Evaluation: Recommend AI tools and platforms based on performance and cost.
- Ethical Oversight: Ensure AI strategies and systems follow ethical principles and minimize risks like bias and privacy issues.
- Documentation: Keep thorough, accurate records of methodologies, architectures, and recommendations.
- As a key team member, foster a positive learning culture by coaching junior staff and sharing best practices and industry knowledge.