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 responsibilitiesDesign and architect end-to-end generative AI systems, including RAG implementationsDevelop Python modules for data science and Machine Learning use casesAnalyze and convert business and process requirements into detailed AI solution specificationsConfigure and manage Azure AI/ML services and orchestrate prompt flow pipelinesAssess AI outputs using metrics such as accuracy and groundednessConstruct and refine prompts to optimize language model performanceCollaborate within an agile multidisciplinary squad and iterate via MVP deliveriesProcess and handle large datasets to support AI training and inferenceDesign conversational interfaces for AI-driven applications Qualifications5-7 years Python development in data science/ML contexts5-7 years implementing RAG frameworks2-4 years working with large language modelsHands-on with Azure AI/ML and prompt orchestrationExperience in prompt engineeringExperience processing large-scale datasetsSkills in conversational UI designFluency in French and English or Dutch and EnglishUnderstanding of utilities sector dynamicsSkills and competences:AI solution architectureRetrieval-Augmented Generation frameworksPython for data science and MLAzure AI/ML and prompt flowPrompt engineeringAI output evaluationLarge dataset managementConversational designAgile collaborationUtilities market knowledge