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
