7 hours, 43 minutes ago

Senior AI Engineer — RAG Applications (Azure / Kubernetes)

Context

STIB-MIVB (Brussels public transport operator) is building several employee- and customer-facing AI services, serving our customers and employees across the organization. The AI services are built and run on our STIB AI Platform.

Your role

We are recruiting a Senior AI Engineer to join the Digital Innovation / AI CoE team for the Build and hypercare phases of some of our most complex AI services. You will work alongside STIB’s internal AI Platform Architect, the other Senior AI Engineer (already on board), and the project teams (project manager, business analyst, solution architect), turning our AI projects into running, evaluated and maintainable services.

The AI Platform runs on a hybrid operating model: managed Azure services (Azure AI Foundry with the OpenAI model family for LLM and embeddings, Azure AI Search, Azure API Management, Azure AI Content Safety) combined with self-hosted open-source components on AKS (agent orchestration in Python with LangChain, ingestion pipeline), with MLflow on Databricks for evaluation and tracing. The Digital Innovation / AI CoE team owns Infrastructure-as-Code for all application-scoped Azure resources, using Terraform and Azure DevOps pipelines.

What you will deliver

Activities will vary from project to project. Typically you will deliver:

  • the RAG pipeline end-to-end, from retrieval strategy to answer generation
  • the ingestion pipeline: connectors to source platforms, chunking, embedding, incremental refresh
  • security trimming and ACL propagation
  • agent orchestration, prompt templates and guardrails
  • the evaluation and tracing setup: offline evaluation sets, retrieval and answer-quality metrics, end-to-end tracing of requests and agent steps
  • the Terraform, Helm and Azure DevOps artefacts needed to deploy and operate the service
  • Observability and cost control: instrumentation for latency, token consumption and run cost, plus quality regression detection after model or prompt changes
  • Hypercare and early production: incident analysis, tuning, runbooks and documentation, and handover of the service to the engineer who will own the Run phase

Apply for this Job

This position was originally posted on Pro Unity.

It is publicly accessible, and we recommend applying directly through the Pro Unity website instead of going through third party recruiters.

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