Join EY and build a remarkable career leveraging global scale, support, and innovative technology. This role focuses on AI Engineering within the AIA - AI / GenAI / Agentic AI career family. We seek an engineer experienced in developing enterprise-grade AI/ML, Generative AI, RAG, conversational AI, and Agentic AI solutions. You will be instrumental in the entire lifecycle, from design and development to deployment and production support, collaborating with diverse teams including architects, data scientists, and business stakeholders. A proven track record of explaining AI implementations, including business impact and technical approach, is essential.

Design, develop, and support advanced AI/ML and Generative AI solutions, including RAG, conversational AI, and AI agents. Build comprehensive pipelines for document ingestion, processing, and retrieval, ensuring effective grounding and prompt orchestration. Develop sophisticated tool-enabled agents and multi-agent workflows utilizing function calling, memory, and enterprise APIs.

Construct scalable backend services using Python, FastAPI, and microservices. Integrate AI solutions with enterprise applications, databases, and cloud platforms. Implement rigorous evaluation metrics for retrieval, accuracy, latency, and cost. Ensure adherence to Responsible AI principles, including PII protection, security, and content safety.

Containerize and deploy services, contributing to CI/CD pipelines and MLOps. Troubleshoot complex issues across the AI ecosystem and prepare detailed technical documentation. Contribute to reusable components and mentor junior team members, fostering engineering excellence.

A minimum of 4-8 years of professional experience in AI/ML, data engineering, or software development is required. Demonstrated hands-on experience in building enterprise-level AI/ML, GenAI, or Agentic AI solutions is crucial. You should have practical experience managing solution components through development, testing, deployment, and operational support.

Core skills include strong proficiency in Python, working knowledge of SQL, data structures, and algorithms. A deep understanding of LLMs, prompt engineering, RAG, embeddings, vector databases, conversational AI, and AI agents is essential. Experience with frameworks like LangChain or AutoGen, along with cloud AI platforms (Azure AI, AWS Bedrock, GCP Vertex AI), is highly valued.

Experience with containerization (Docker, Kubernetes), CI/CD, MLOps, and LLMOps is necessary. A solid understanding of Responsible AI principles, security, and data privacy is also critical. Frontend experience with React and TypeScript, especially for chat interfaces, is preferred. Excellent analytical, communication, and collaboration skills are a must.