Senior AI Engineer— RAG Applications (Azure / Kubernetes) …, Brussels

Job Opportunity: Senior Artificial Intelligence (AI) Engineer Location:

Bruxelles (Cantersteen)

Duration:

ASAP– 31/12/2026 (Initial 9-month contract with potential extension up to 880 working days)

Work Arrangement:

Full-time Role Overview

We are seeking a highly skilled

Senior AI Engineer

to join a leading Digital Innovation / AI Center of Excellence (CoE) team. This role is pivotal for the "Build" and early "Run" phases of a flagship RAG-based (Retrieval-Augmented Generation) knowledge search service. Serving approximately 10,000 employees, this bilingual (French/Dutch) AI solution is the first production service on a newly established enterprise AI Platform. You will work in close collaboration with the internal AI Platform Architect and Solution Architect to transform high-level designs into a robust, evaluated, and maintainable production service.Key Responsibilities

1. RAG Pipeline Development

End-to-End Implementation:

Build and optimize the full RAG lifecycle, including sophisticated retrieval strategies, reranking logic, LLM orchestration, and precise citation handling. Ingestion&Processing:

Develop high-performance ingestion pipelines featuring connectors for

Jahia CMS

and

SharePoint

. Data Engineering:

Implement intelligent document chunking, embedding generation, and management of vector stores. 2. Infrastructure&Deployment

Hybrid Cloud Management:

Operate within a hybrid environment utilizing managed

Azure

services (OpenAI, API Management, Content Safety) and self-hosted open-source components on

Azure Kubernetes Service (AKS)

. Infrastructure as Code (IaC):

Own and manage application-scoped Azure resources using

Terraform

and

Azure DevOps

CI/CD pipelines. Containerization:

Develop and maintain

Helm

charts for service deployment on AKS. 3. Quality, Security&Governance

Security&Compliance:

Implement rigorous security trimming and Access Control List (ACL) propagation to ensure data privacy. Prompt Engineering:

Design and refine prompt templates and integrated guardrails to ensure output accuracy and safety. Evaluation:

Build and maintain an evaluation harness to systematically measure and improve model performance (accuracy, relevancy, and groundedness). Technical Profile&Requirements

Core Engineering Skills

Python:

Advanced proficiency; ability to write clean, scalable, and production-ready code. Terraform:

Advanced expertise in Infrastructure-as-Code for Azure environments. Azure Kubernetes Service (AKS):

Advanced experience in deploying and managing containerized applications. Azure DevOps:

Advanced skills in managing pipelines and automated releases. AI&LLM Expertise

RAG (Retrieval-Augmented Generation):

Intermediate to Advanced understanding of RAG architectures and optimization. LLMs:

Practical experience working with Large Language Models (specifically Azure OpenAI Service). Vector Databases:

Solid understanding of vector storage, indexing, and retrieval mechanics. Language Requirements

French or Dutch:

Native or bilingual proficiency (the service is bilingual). English:

Full professional proficiency for technical collaboration and documentation. What to Expect

This is a mission-critical project where you will transition from initial development into the early operational tuning phase. You will be a key contributor to an AI CoE that is setting the standard for future AI services within a large-scale public organization.

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