We are looking for a
Senior AI Engineer specialized in Generative AI and Retrieval-Augmented Generation (RAG)
to join a strategic project within a European institution. You will play a key role in designing and building AI-powered assistants and intelligent knowledge platforms supporting institutional staff in accessing, understanding, and leveraging large volumes of information efficiently.
This role is ideal for hands-on AI engineers with strong experience in LLMs, RAG pipelines, and production-grade AI systems.
Key Responsibilities
Design, build and deploy AI-powered assistants and Generative AI solutions.
Architect and implement Retrieval-Augmented Generation (RAG) pipelines.
Develop LLM orchestration flows, prompt strategies, and retrieval mechanisms.
Integrate Large Language Models (LLMs) using APIs and open-source frameworks.
Perform data ingestion, preprocessing, cleansing and structuring for AI pipelines.
Experiment with retrieval strategies, embeddings, vector databases, and prompt engineering to optimize quality and performance.
Evaluate AI outputs and continuously refine model responses.
Contribute to data engineering pipelines supporting AI solutions.
Deploy and scale AI services using cloud platforms (AWS or Azure).
Ensure security, compliance, scalability, performance, and reliability of AI systems.
Collaborate closely with business stakeholders, IT teams, and data engineers.
Required Skills & Experience
Generative AI & Data Engineering
Strong hands-on experience building Generative AI applications.
Proven experience with Retrieval-Augmented Generation (RAG) architectures.
Solid experience working with LLMs (OpenAI, Azure OpenAI, open-source models).
Strong expertise in prompt engineering and orchestration workflows.
Experience with vector databases (Pinecone, Weaviate, Qdrant, FAISS, Chroma, etc.).
Experience with LangChain, LlamaIndex, or similar frameworks.
Strong Python programming skills.
Experience in data preprocessing, ingestion, and transformation pipelines.
Experience deploying AI workloads on AWS or Azure.
Solid knowledge of SQL, NoSQL, and data storage systems.
Technical Environment (Nice to Have)
FastAPI / Flask
Docker & Kubernetes
CI/CD pipelines
MLflow, model monitoring & evaluation tools
Azure OpenAI / AWS Bedrock
Elasticsearch, OpenSearch
Education & Experience
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering or related field.
5+ years of professional experience, with strong focus on AI / ML / Generative AI systems.
Languages
English: C1 (mandatory)
Work Model
Hybrid – Brussels