GenAI Data Scientist: RAG Solutions in Azure

Digitribe; Belgique; Remote; EUR 70,000 - 100,000; Full time

Job summary

DigiTribe in Belgium is seeking a GenAI Data Scientist to turn AI opportunities into secure business solutions. You will design, prototype and industrialise use cases based on LLMs and Retrieval-Augmented Generation (RAG), with a focus on Azure environments.

You will collaborate with business stakeholders to scope opportunities, build end-to-end RAG pipelines, evaluate performance, and move prototypes into production following MLOps practices while upholding privacy and compliance.

Qualifications

• ≥3 years of experience in data science or ML with GenAI/LLM projects.
• Hands-on building RAG pipelines with LangChain, LlamaIndex or Semantic Kernel.
• Strong Python skills and NLP/ML fundamentals.
• Experience with Azure AI services (Azure OpenAI, Azure AI Search).
• Ability to explain AI concepts and risks to non-technical audiences.
• Fluent in English and either French or Dutch.

Responsibilities

• Identify and scope GenAI use cases with business stakeholders.
• Design and build RAG solutions covering ingestion, chunking, embeddings, vector search and prompt engineering.
• Develop solutions with Azure OpenAI, Azure AI Search, Azure Machine Learning and related services.
• Evaluate model performance, including answer quality, hallucination control and relevance metrics.
• Move prototypes into production with engineering teams, following MLOps/LLMOps practices.
• Ensure responsible AI, data privacy, security and compliance with regulations such as EU AI Act and GDPR.
• Share knowledge and raise AI maturity within client teams.

Skills

Python

NLP

Machine Learning

Communicating AI concepts

English

French

Dutch

Tools

LangChain

LlamaIndex

Semantic Kernel

Azure OpenAI

Azure AI Search

Azure Machine Learning

Databricks

Microsoft Fabric

Vector databases

Job description

DigiTribe in Belgium is seeking a GenAI Data Scientist to turn AI opportunities into secure business solutions. You will design, prototype and industrialise use cases based on LLMs and Retrieval-Augmented Generation (RAG), with a focus on Azure environments.

You will collaborate with business stakeholders to scope opportunities, build end-to-end RAG pipelines, evaluate performance, and move prototypes into production following MLOps practices while upholding privacy and compliance.