Location: Brussels Languages: English and Dutch/French Employment Type: Freelance Start Date: ASAP End Date: 31/12/2026 Context of the mission/Objective(s) of the job: The client is developing UGo AI Search, a RAG-based bilingual (French/Dutch) enterprise knowledge search platform designed to serve ~10,000 employees. This is the first production-grade AI service on the client’s AI Platform and will pave the way for multiple future AI solutions. You will join the Digital Innovation / AI Center of Excellence (AI CoE) team during the Build and early Run phases, contributing to the successful delivery, deployment, and optimization of this strategic initiative. The AI Platform follows a hybrid architecture, combining: Managed Azure services (Azure OpenAI, API Management, Content Safety) Self-hosted open-source components on Azure Kubernetes Service (AKS) Infrastructure is managed via Terraform and Azure DevOps pipelines. Your Role. As a Senior AI Engineer, you will translate high-level architectural designs into a fully functional, scalable, and maintainable AI service. You will work closely with: AI Platform Architect UGo AI Search Solution Architect Your focus will be on building, deploying, and optimizing the RAG-based system, ensuring it meets enterprise-grade performance, security, and reliability standards. What you will deliver. End-to-end implementation of the RAG pipeline, including: Retrieval and re-ranking LLM orchestration Citation handling Development of the data ingestion pipeline : Integration with Jahia CMS and SharePoint Document chunking and embedding workflows Implementation of: Security trimming and ACL propagation Prompt templates and guardrails Creation of an evaluation and benchmarking framework for model performance Development and maintenance of: Infrastructure-as-Code (Terraform) Deployment artefacts (Helm charts) Contribution to: Deployment, monitoring, and tuning during early Run phase Continuous improvement of system performance and reliability Key Responsibilities Build scalable and production-ready AI pipelines using RAG architecture Collaborate with architects to translate designs into implementation Ensure secure and compliant access to enterprise knowledge sources Optimize retrieval quality, latency, and response accuracy Automate deployment pipelines and infrastructure provisioning Monitor, debug, and improve system performance post-deployment Contribute to best practices within the AI CoE Required Skills & Experience Core Technical Skills Python – Advanced (recent hands-on experience) Azure DevOps – Advanced Azure Kubernetes Service (AKS) – Advanced Terraform – Advanced AI / ML Expertise RAG (Retrieval-Augmented Generation) – Intermediate LLMs (Large Language Models) – Intermediate Azure OpenAI Service – Intermediate Vector Databases – Intermediate