Join EY's GDS AI & Data team and help clients navigate complex challenges using cutting-edge AI, Automation, and Data Engineering. This role focuses on driving value and uncovering opportunities across diverse sectors like Banking, Insurance, Healthcare, and Manufacturing.

We are seeking a talented Manager, Forward Deployed Engineer, with a minimum of 9 years of hands-on experience in designing, building, and deploying AI solutions directly with clients. This position is ideal for a driven individual contributor who excels in ambiguous environments, prefers direct system building over team management, and can effectively translate intricate business problems into production-ready AI solutions. Expertise in GenAI, AI/ML, and Data Science across various enterprise AI platforms and hyperscalers is essential.

Lead the end-to-end deployment of advanced AI and GenAI solutions at strategic client locations. You will be instrumental in the discovery, design, development, and implementation of high-impact AI solutions in close collaboration with client stakeholders.

Key responsibilities include building LLM-driven applications, RAG systems, and agentic workflows to deliver tangible business value. Drive innovation by developing reusable accelerators, frameworks, and reference implementations for enterprise GenAI deployments. Furthermore, you will enable rapid experimentation and widespread adoption of AI, data, and cloud platforms through hands-on engineering leadership.

Partner effectively with client business and engineering teams to translate complex challenges into actionable GenAI solutions. You will own the complete solution delivery lifecycle, from initial discovery and architecture to final production deployment.

Serve as a trusted technical advisor to senior client leadership. Design and construct LLM-powered applications, such as copilots, assistants, RAG systems, and agentic workflows. Integrate GenAI solutions seamlessly with enterprise data platforms, APIs, and external systems. Optimize solutions for performance metrics including latency, cost, accuracy, scalability, security, and compliance.

Transform Proofs of Concept (PoCs) into robust, enterprise-ready platforms through agile iteration and feedback. Architect scalable, reliable, and observable systems utilizing cloud-native patterns. Develop reusable accelerators, reference architectures, and best practices to facilitate enterprise GenAI adoption.