Join an agile cross-functional team to translate business needs into AI solution specifications, design and implement generative AI architectures with retrieval-augmented generation, develop Python-based ML components, orchestrate Azure AI/ML and prompt workflows, evaluate model outputs using key metrics, engineer prompts, process large datasets, and craft conversational interfaces. Key responsibilities Design and architect end-to-end generative AI systems, including RAG implementations Develop Python modules for data science and Machine Learning use cases Analyze and convert business and process requirements into detailed AI solution specifications Configure and manage Azure AI/ML services and orchestrate prompt flow pipelines Assess AI outputs using metrics such as accuracy and groundedness Construct and refine prompts to optimize language model performance Collaborate within an agile multidisciplinary squad and iterate via MVP deliveries Process and handle large datasets to support AI training and inference Design conversational interfaces for AI-driven applications Qualifications 5-7 years Python development in data science/ML contexts 5-7 years implementing RAG frameworks 2-4 years working with large language models Hands-on with Azure AI/ML and prompt orchestration Experience in prompt engineering Experience processing large-scale datasets Skills in conversational UI design Fluency in French and English or Dutch and English Understanding of utilities sector dynamics Skills and competences: AI solution architecture Retrieval-Augmented Generation frameworks Python for data science and ML Azure AI/ML and prompt flow Prompt engineering AI output evaluation Large dataset management Conversational design Agile collaboration Utilities market knowledge