RAG Engineer
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What you will do
- Design, build and maintain scalable RAG pipelines covering ingestion, chunking, embeddings, retrieval and generation.
- Build ingestion and refresh flows using Azure Data Lake, Databricks and Azure Data Factory.
- Select and optimise vector stores, embedding models, hybrid search and reranking approaches.
- Work with multilingual documents, scanned PDFs, tables and different document and product versions.
- Evaluate and improve retrieval and generation quality using metrics, human review and RAG evaluation frameworks.
- Collaborate with data engineers, data scientists, ML engineers and business analysts to productionise AI use cases.
- Implement monitoring, feedback loops and continuous improvement, including cost and latency tracking.
- Apply GDPR, responsible-AI, access-control and document-level security principles.
What you bring
- A university degree in computer science, data science, AI/ML, statistics or a similar quantitative/technical discipline; a Master's is preferred.
- At least 3 years of experience in data, ML or GenAI engineering, including hands-on RAG or retrieval experience.
- Strong experience with Python, SQL and Spark.
- Experience with Azure, including relevant services such as Data Lake, Databricks, Synapse, Azure OpenAI and AI Search.
- Experience with an LLM orchestration framework such as LangChain, LlamaIndex or Semantic Kernel, or a similar framework.
- Strong communication skills and the ability to explain technical topics to both technical and non-technical stakeholders.
- Excellent command of Dutch, French and English.
- Ability to work independently and collaboratively while managing multiple priorities.
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