EY - GDS Consulting - AIA - AI Engineer- Senior

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.

AI Engineer-GenAI, Agentic AI, RAG and Enterprise AI Engineering Career Family: AIA - AI / GenAI / Agentic AI   The opportunity We are seeking an AI Engineer with strong hands-on experience building enterprise-grade AI/ML, Generative AI, RAG, conversational AI and Agentic AI solutions. The engineer will contribute across design, development, testing, deployment, observability and production support, working closely with architects, data scientists, application engineers, UX teams, security teams and business stakeholders. The successful candidate must be able to explain at least one or two enterprise, pre-production or production AI implementations, including the business use case, individual contribution, technical approach, controls and outcomes. Certifications, personal projects and demonstrations alone are not sufficient.   Your key responsibilities

Design, develop, test and support AI/ML, GenAI, RAG, conversational AI, copilot and AI-agent solutions aligned with business and architecture requirements. Build document ingestion, parsing, chunking, embedding, indexing, retrieval, reranking, grounding and prompt-orchestration pipelines. Develop tool-enabled agents and multi-agent workflows using function calling, memory, enterprise APIs and human-in-the-loop patterns. Build scalable backend services and integrations using Python, FastAPI, REST APIs, microservices, asynchronous processing and event-driven patterns. Develop or integrate modern user experiences for chatbots, copilots and agents using React, TypeScript or equivalent frameworks when required. Implement real-time AI interactions using WebSockets, Server-Sent Events or token streaming, including safe rendering and resilient error handling. Integrate AI solutions with enterprise applications, workflow platforms, databases, vector stores, search services and cloud data platforms. Implement evaluation and quality checks for retrieval, groundedness, accuracy, hallucination risk, prompt performance, tool execution, latency and cost. Apply Responsible AI, PII protection, access controls, data privacy, secure coding, prompt-injection mitigation, content safety and auditability controls. Containerize and deploy services, contribute to CI/CD pipelines, automated tests, monitoring, logging, release management and production support. Troubleshoot issues across data pipelines, models, prompts, agent workflows, APIs, vector stores, streaming services and user interfaces. Prepare technical designs, implementation notes, test evidence, runbooks, solution walkthroughs and delivery updates. Contribute reusable components, SDKs, accelerators and engineering standards; guide junior team members where required.

Skills and attributes Professional experience

4-8 years of overall professional experience in AI/ML, data engineering, cloud engineering, software development or related fields. Hands-on experience contributing to enterprise or client-facing AI/ML, GenAI, copilot, conversational AI, Agentic AI or RAG solutions. Practical experience taking solution components through development, testing, deployment and operational support. Ability to collaborate effectively with architects, managers, product owners, engineers and business stakeholders.

Core AI and engineering skills

Strong proficiency in Python and working knowledge of SQL, data structures, algorithms, software engineering and object-oriented design. Strong understanding of LLMs, prompt engineering, RAG, embeddings, semantic and hybrid search, vector databases, conversational AI and AI agents. Hands-on experience with