AI Agentic Engineer - Senior

Role Overview: As an AI Enabled Automation Developer Senior at EY, you will have the opportunity to build a unique career tailored to your skills and interests. You will be part of a global team that provides support, fosters an inclusive culture, and leverages cutting-edge technology to help you reach your full potential. Your individual voice and perspective are valued contributions that will help EY enhance its services and make a positive impact on the working world. Key Responsibilities: - Develop and implement AI-enabled automation solutions that align with business objectives. - Design and deploy Proof of Concepts (POCs) and Points of View (POVs) in various industry verticals to showcase the potential of AI-enabled automation applications. - Ensure seamless integration of optimized solutions into the overall product or system. - Collaborate with cross-functional teams to understand requirements, integrate solutions into cloud environments (Azure, GCP, AWS, etc.), and ensure alignment with business goals and user needs. - Educate the team on best practices and stay informed about the latest technological advancements to bring innovative solutions to the project. Qualifications Required: - 4 to 7 years of relevant professional experience. - Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. - Strong foundation in ML algorithms, feature engineering, and model evaluation. - Solid understanding of Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP. - Experience in GenAI technologies such as LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. - Familiarity with LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI. - Knowledge of retrieval augmented generation (RAG) and Knowledge Graph RAG. - Experience with multi-agent orchestration, memory, and tool integrations. - Experience implementing MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning, and reproducibility). - Proficiency in cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. - Understanding of data pipelines, APIs, and distributed systems. - Ability to build observability into AI systems, monitoring latency, drift, and performance metrics. - Strong written and verbal communication, presentation, client service, and technical writing skills in English for both technical and business audiences. - Strong analytical, problem-solving, and critical thinking skills. - Ability to work under tight timelines for multiple project deliveries. (Note: The additional details of the company were not found in the provided job description.),