RAG: Understanding or implementation experience with Retrieval-Augmented Generation (RAG), including document chunking, embeddings, vector search, and retrieving relevant context.
Integrate the digital stack. Connect models and AI services with enterprise platforms, data sources, workflow systems, user interfaces and upstream or downstream applications.
· Work with product owners, engineering teams, and industry partners throughout the product development lifecycle from concept, design, prototyping, acceptance testing, data curation, delivery, operationalisation, industry proliferation, to product end-of-life
Experience of working in a multicultural, multidisciplinary and multi-ethnic environment, contributing to the development of mutual understanding, trust and tolerance
Infrastructure & Engineering Excellence: Manage infrastructure and CI/CD pipelines while ensuring scalability, performance, security, and high code quality through best practices and governance.
Collaborate closely with Product, ML/Algorithm, and Design teams to align prompts with product feature logic, ensuring quality and stability across critical user journeys.