EY-Consulting-GenAI/Agentic – Senior Manager

We are looking to hire individuals with 16+ years of relevant professional experience with strong AI Enabled Automation skills who are interested in applying AI in the process automation space – Azure, AWS, AI, ML, Deep Learning, NLP, GenAI, large Language Models (LLM), RAG, Vector DB, Graph DB, and Python.

Responsibilities:

• Provide strategic direction and leadership to project teams, fostering a culture of innovation and continuous improvement.
• Manage stakeholder relationships, ensuring clear communication and alignment on project goals and deliverables.
• Drive team performance by setting clear objectives, providing feedback, and supporting professional development.
• Lead the 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.
• Collaborate with cross-functional teams to understand requirements, integrate solutions into cloud environments (Azure, GCP, AWS, etc.), and ensure alignment with business goals and user needs.
• Educate and mentor team members on best practices and keep updated on the latest tech advancements to bring innovative solutions to projects.

Technical Skills Requirements:

• Proven experience driving GenAI and LLM-enabled solutions (GPT, Claude, LLaMA) across the full lifecycle—from use‑case identification, prompting strategies, governance/safety, and tuning to enterprise deployment.
• Delivery leadership experience with Agentic AI frameworks such as LangChain, LlamaIndex, LangGraph, AutoGen, and CrewAI, capable of designing and supervising multi‑agent workflows that integrate into enterprise automation ecosystems.
• Strong understanding of RAG architectures, including Knowledge‑Graph‑enhanced RAG, with the ability to oversee platform‑level integrations and assure engineering rigor.
• Experience guiding teams in multi‑agent orchestration, memory persistence, tool integrations, and safe‑execution patterns essential for enterprise Agentic AI deployments.
• Strong practical understanding of deploying scalable ML/GenAI solutions on Azure, AWS, and GCP, overseeing cloud-native solution design and performance optimization.
• Leadership-level understanding of data pipelines, API ecosystems, distributed systems, and integration patterns necessary for enterprise-grade AI delivery.
• Ability to define and govern AI observability frameworks, including monitoring for latency, drift, reliability, and overall system performance, ensuring stability in production environments.
• Strong communication and consulting skills, capable of articulating complex AI constructs to clients, leading executive discussions, and ensuring high-quality deliverables across technical and business audiences
• Advanced analytical, problem‑solving, and structured thinking skills for guiding architecture decisions, resolving delivery bottlenecks, and ensuring high-quality outcomes.