EY - GDS Consulting - AI and DATA - Forward Deployed engineer - Associate Director

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

EY- GDS – AI & Data – Associate Director – Forward Deployed Engineer As part of our EY-GDS AI & Data team, we help our clients solve complex business challenges with the help of AI, Automation, Data Engineering technology. We drive value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance.   The opportunity We are seeking a Associate Director for Forward Deployed Engineer (FDE) with 15+ years of deep, hands-on engineering experience to design, build, and deploy AI-powered solutions directly with clients . This role is ideal for an elite individual contributor who thrives in ambiguous environments, prefers building real systems over managing teams, and can translate business problems into production-grade AI solutions. The individual should have worked on GenAI, AI/ML, Data Science solutions on multiple proprietary enterprise AI tech stacks along with Hyperscalers, Platform AI tech stack.   Role Purpose:

Lead complex end-to-end deployments in production at strategic customers. Act as a forward-deployed technical owner, responsible for taking ambiguous ideas from concept → prototype → production. Lead the discovery, design, development, and deployment of high-impact AI / GenAI-powered solutions in close collaboration with client stakeholders. Build LLM-driven applications, RAG systems, and agentic workflows that demonstrate measurable business value. Drive innovation by creating reusable accelerators, frameworks, and reference implementations for enterprise GenAI deployments. Enable rapid experimentation and large-scale adoption of AI, data, and cloud platforms through hands-on engineering leadership.

Embed directly with clients to understand business and technical challenges. Break down vague or high-level problem statements into executable engineering solutions. Own solution outcomes end-to-end, from discovery to production deployment. Operate as a trusted technical advisor to senior client stakeholders. Design and build LLM-powered applications (chatbots, copilots, assistants), Retrieval-Augmented Generation (RAG) systems & Agentic workflows and orchestration pipelines Integrate LLMs with enterprise data platforms, APIs, and external systems. Evaluate and optimize trade-offs across latency, cost, accuracy, scalability, and security. Iterate rapidly based on client feedback. Convert PoCs into production-grade, enterprise-ready deployments. Design systems for scalability, reliability, and observability. Build reusable engineering accelerators, frameworks, and reference architectures. Codify best practices for enterprise GenAI deployments. Collaborate with internal teams to transition deployed solutions into long-term support and scale. Develop cloud-native architectures across Azure, AWS, or GCP.

Required Skills & Experience Mandatory

15+ years of experience in software engineering, data engineering, or AI/ML. Strong hands-on system-building and production deployment experience. Proven experience delivering solutions in client-facing or high-ambiguity environments. Solid understanding of Distributed systems, Microservices and APIs & Cloud-native architectures Ability to independently own and deliver complex, high-impact solutions. Excellent communication skills with both technical and business stakeholders.

Desired / Preferred

Hands-on experience with LLM APIs and prompt engineering, RAG architectures and vector databases, Agentic workflows and orchestration