Join EY's AI and Data practice as a Senior Manager and architect cutting-edge AI and data solutions for a diverse clientele. You'll leverage your extensive experience in AI/ML, Generative AI, and Agentic AI to drive client success and shape the future of technology transformation. This role offers a unique opportunity to collaborate with global stakeholders and lead impactful projects within a leading consulting firm.

EY is committed to fostering a culture of innovation, continuous learning, and personal development. We empower our professionals to build unique careers, supported by global scale and inclusive culture. Become the best version of yourself while contributing to a better working world for all.

Spearhead consultative selling, partnering with C-suite leaders to identify AI-driven transformation opportunities and articulate compelling value propositions.

Architect end-to-end AI, Generative AI, and Agentic AI solutions across major cloud platforms (Azure, AWS, GCP), utilizing advanced AI platforms and frameworks like OpenAI, LangChain, and vector databases.

Design enterprise AI architectures, including RAG patterns, autonomous agent workflows, and LLMOps for scalable cloud-native deployments.

Provide technical leadership and oversight for AI/GenAI project delivery, ensuring architecture integrity, quality, and alignment with business objectives.

Drive innovation through the development of proofs of concept, accelerators, and thought leadership in AI strategy and best practices.

A minimum of 16 years of professional experience, including 5-8 years architecting and deploying enterprise-scale AI/ML, GenAI, and Agentic AI solutions. Possess extensive pre-sales and consultative experience, with a proven ability to diagnose business problems and connect AI capabilities to measurable business impact.

Demonstrate deep expertise in designing AI solutions using microservices and cloud-native architectures, with a strong understanding of Agentic AI, AI-ready data, and enterprise-scale LLM solution patterns (RAG, agents, orchestration).

Proficiency in hands-on AI/ML solution deployment on Azure, AWS, and/or GCP, with a solid understanding of platform-native services and LLM orchestration across cloud platforms. Experience in MLOps/LLMOps/AgentOps toolchains and Responsible AI principles is essential.

Hold a Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field. Strong programming skills in Python are required for prototyping and validation.