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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 Lang Chain, Llama Index, Lang Graph, Auto Gen, 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.

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