Artificial Intelligence Engineer

Key responsibilities - Drive continuous RAG model improvement - Improve retrieval performance, answer quality and overall user experience through experimentation, analysis and optimization. - Build evaluation and measurement capabilities - Develop automated frameworks that measure RAG quality, identify regressions and provide actionable insights for future improvements. - Turn insights into production outcomes - Translate data analysis and experimentation results into scalable, maintainable engineering solutions that deliver measurable business value. - Together we achieve more than alone - The RAG platform is not a research project. It is a production product that must continuously improve. - You will join a team of experienced engineers who are building and operating critical AI capabilities within Client. Success in this role comes from combining scientific rigor with engineering excellence. We value people who challenge assumptions, validate ideas through data and continuously raise the quality bar. You & your talent - We are looking for someone who enjoys solving hard problems and is driven by measurable outcomes. Someone who is equally comfortable discussing statistical significance, retrieval metrics and system architecture. - You take ownership of results rather than activities. You are naturally curious, analytical and passionate about improving complex systems. Mandatory skills - Retrieval-Augmented Generation (RAG); - Large Language Models (LLMs); - Python; - Databricks; - Evaluation frameworks for GenAI systems; - Embedding models; - Prompt optimization; - Data pipelines and workflow automation; - CI/CD practices; - Azure.