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
