Atcon Global - Senior AI Engineer - RAG Application

End Date: 31/12/2026

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