EY - GDS Consulting - AIA - Agentic AI Engineer- Senior

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Career Family:  AIA – AGENTIC AI ENGINEER  The opportunity We are seeking a dynamic Senior Consultant to join our AI & Data Consulting team, focused on building enterprise-grade GenAI and Agentic AI solutions with strong emphasis on LLM engineering, frontend experience layer, reusable UI components, and real-time copilot interfaces . The ideal candidate will bring a strong combination of AI engineering, LLM application development, agentic AI system design, backend engineering, and modern frontend development expertise . This role requires hands-on experience in building chatbots, copilots, agent-driven workflows, reusable UI SDKs, streaming interfaces, and API-driven AI experiences that are scalable, secure, maintainable, and production-ready . You will work closely with AI engineers, backend engineers, UX designers, product owners, security teams, platform teams, and business stakeholders to design and implement LLM-powered applications, agentic workflows, Retrieval-Augmented Generation (RAG) pipelines, streaming AI interfaces, and reusable experience-layer components that accelerate enterprise AI adoption and business transformation.   Your key responsibilities Technical Excellence:

AI Engineering & Agentic AI Development

Design and develop enterprise-grade GenAI and Agentic AI applications using LLM frameworks such as LangChain, LangGraph / AutoGen / Google Agent SDK, and Model Context Protocol (MCP). Build agentic AI architectures including multi-agent workflows, tool/function calling, enterprise integrations, memory patterns, and autonomous decision flows. Develop and maintain Retrieval-Augmented Generation (RAG) pipelines including document ingestion, chunking, embeddings generation, vector indexing, retrieval optimization, and response grounding. Implement semantic search and knowledge retrieval solutions using vector databases and hybrid search patterns. Develop prompt engineering strategies, tool-based agents, AI workflows, and enterprise copilots aligned to business use cases. Contribute to AI evaluation, observability, monitoring, and performance optimization of LLM-powered applications. Stay current with emerging trends in GenAI, Agentic AI, LLM frameworks, AI SDKs, multimodal AI, and enterprise AI engineering practices.

Frontend & Experience Layer Engineering

Design and build modern AI user experiences using React, TypeScript, Next.js, reusable UI component libraries, and frontend SDKs. Develop chatbot, copilot, and agent-driven interfaces that provide intuitive, responsive, and accessible user experiences. Build reusable React and TypeScript components and SDKs that can be consumed across multiple applications and teams. Implement state management, client-side performance optimization, accessibility standards, and design system integration for enterprise-grade AI applications. Develop API-first and contract-driven UI integrations with backend services, agent APIs, and streaming endpoints. Implement extensible plug-in patterns, schema-driven forms, typed API clients, and component-driven architectures for scalable AI experiences.

Streaming & Real-time UI Development

Implement real-time AI interfaces using WebSocket’s, Server-Sent Events (SSE), and token-level LLM response streaming. Build streaming chat, copilot, and agent interfaces with incremental rendering, backpressure handling, and low-latency response patterns. Develop real-time visualization of agent state, workflow progress, tool usage, and execution traces. Optimize streaming performance across frontend, backend, and LLM service layers.