Typical Day in Role:

• Determine the right tool for the job—balancing the precision of deterministic AI with the flexibility of RAG and AI models.
• Gather and clean relevant data sets for training and fine‑tuning Large Language Models (LLMs), and building Retrieval Augmented Generation (RAG) systems.
• Ensure data quality, consistency, and compliance with regulatory requirements.
• Develop and fine‑tune specialized Large Language Models (LLMs) and advanced Natural Language Understanding (NLU) techniques for diverse banking use cases, including complex information extraction, multi‑turn dialogue management, and financial text summarization.
• Design, develop, and optimize intelligent, agentic conversational AI systems (e.g., advanced virtual assistants, automated financial advisors) leveraging LLMs for seamless customer interactions across various channels, including text and voice.
• Implement and refine advanced Natural Lang...