Your responsibilities will include:
- Identify and scope GenAI use cases with business stakeholders, such as knowledge assistants, document analysis and process automation.
- Design and build RAG solutions, covering document ingestion, chunking, embeddings, vector search and prompt engineering.
- Develop solutions with Azure OpenAI, Azure AI Search, Azure Machine Learning and related services.
- Evaluate and improve model performance, including answer quality, hallucination control and relevance metrics.
- Move prototypes into production with engineering teams, following MLOps/LLMOps practices.
- Ensure responsible AI principles, data privacy, security and compliance with regulations such as the EU AI Act and GDPR.
- Share knowledge and help raise AI maturity within client teams.
What we’re looking for
The ideal candidate will have:
- At least 3 years of experience in data science or machine learning, with recent hands-on work on GenAI/LLM projects.
- Practical experience building RAG pipelines, using frameworks such as LangChain, LlamaIndex or Semantic Kernel.
- Strong Python skills and a solid grounding in NLP and machine learning fundamentals.
- Experience with Azure AI services such as Azure OpenAI and Azure AI Search.
- Ability to explain AI concepts, limits and risks to non-technical audiences.
- Fluent English, French and/or Dutch.
Nice to have:
- An Azure AI certification (AI-102 or DP-100).
- Experience with vector databases, agentic workflows, fine-tuning or LLM evaluation frameworks.
- Experience with Databricks or Microsoft Fabric.
- Experience in banking, insurance or other regulated sectors.
