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