EY - GDS Consulting - AIA - Gen AI - Manager

Overview

Other locations:
Primary Location Only

Date:
Jan 29, 2026

Requisition

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.

EY-Consulting – AI Enabled Automation
-GenAI/Agentic – Manager

• Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives.
• Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications.
• Ensure seamless integration of optimized solutions into the overall product or system
• Collaborate with cross-functional teams to understand requirements, to integrate solutions into cloud environments (Azure, GCP, AWS, etc.) and ensure it aligns with business goals and user needs
• Educate team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project

• 9 to 13 years of relevant professional experience Proficiency in Python and frameworks like PyTorch, Tensor Flow, Hugging Face Transformers.
• Strong foundation in ML algorithms, feature engineering, and model evaluation.
  
  - Must
• Strong foundation in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP.
  
  -Must
• Experience in GenAI technologies — LLMs (GPT, Claude, LLaMA), prompting, fine-tuning.
• Experience with Lang Chain, Llama Index, Lang Graph, Auto Gen, or CrewAI.(Agentic Framework)
• Knowledge of retrieval augmented generation (RAG)
• Knowledge of Knowledge Graph RAG
• Experience with multi-agent orchestration, memory, and tool integrations
• Experience/Implement MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning and reproducibility)--Good to have
• Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment.
• Good understanding of data pipelines, APIs, and distributed systems.
• Build observability into AI systems — latency, drift, performance metrics.
• Strong written and verbal communication, presentation, client service and technical writing skills in English for both technical and business audiences.
• Strong analytical, problem solving and critical thinking skills.
• Ability to work under tight timelines for multiple project deliveries.