Join EY's GDS Consulting team as a Senior Manager in the AIA Gen AI practice. This role is for an experienced AI Architect passionate about Data & Analytics and technology. You will be instrumental in developing and implementing cutting-edge AI capabilities and solutions.

We are seeking an individual with a deep understanding of data processing, data structures, algorithms, and machine learning. This position offers the opportunity to build a career within a global, inclusive culture, leveraging EY's extensive support and technology resources to achieve your full potential.

Be a part of a dynamic team that drives innovation and delivers exceptional experiences for clients worldwide. Your unique perspective will contribute to EY's continuous improvement and help shape a better working world for everyone.

As an AI Architect, you will design and implement advanced AI and Generative AI applications, systems, and infrastructure on major cloud platforms like Azure, AWS, and GCP. You will collaborate closely with data engineers and scientists to create robust data pipelines and AI/ML models.

Key responsibilities include translating business requirements into scalable solutions, contributing to architectural decisions for industry-wide use cases, and establishing engineering best practices. You will identify opportunities for generative AI to solve complex business problems, create proof-of-concepts, and write high-quality, efficient code.

Furthermore, you will stay abreast of the latest AI trends, evaluate state-of-the-art technologies, facilitate design workshops, and mentor AI engineers. You will also manage end-to-end project delivery, ensuring solutions meet client expectations and effectively communicating with stakeholders.

We are looking for an experienced AI Architect with a minimum of 15 years of professional experience, including 5-8 years in building and deploying AI solutions on cloud platforms. A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field is required.

Technical expertise should include MLOps, LLMOps, and AgentOps architecture design, deploying AI/ML solutions on Azure, AWS, and GCP, and orchestrating LLM models. Proficiency in Python/PySpark, SQL, data modeling, and microservices architecture is essential. A strong background in Azure-based AI and data technologies is a must.

Candidates must possess excellent problem-solving and communication skills, with the ability to connect AI capabilities to business value. Familiarity with AI/ML solution deployment processes and responsible AI concepts is also required. Experience with code versioning, MLFlow, and CI/CD tools is advantageous.