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Senior AI Engineer for RAG Solutions on Azure and Kubernetes (Employed or freela

EngiFlex
On-site
Posted 4 days ago
AI-Engineer

AI summary

This role involves building and maintaining complex AI services on Azure and Kubernetes, focusing on the deployment and operational phases with a strong emphasis on AI initiatives, integration, and observability.

Eligible from: Unclear

Job Description

📋 Tasks and responsibilities

This role focuses on the build and hypercare phases of complex AI services used by both employees and customers across the organization.

You will work closely with an internal AI Platform Architect, another senior AI engineer and project teams including project management, business analysis and solution architecture. Your objective is to turn AI initiatives into operational, measurable and maintainable services.

The environment combines managed Azure services with open-source components running on AKS. It includes Azure AI Foundry with Azure OpenAI models for LLM use cases and embeddings, Azure AI Search, Azure API Management and Azure AI Content Safety, alongside Python-based agent orchestration with LangChain, ingestion services on AKS, and MLflow on Databricks for evaluation and tracing. Infrastructure-as-Code for application-level Azure resources is managed with Terraform and Azure DevOps pipelines.

What you will deliver

Your activities may differ by project, but typically include:

  • building the end-to-end RAG pipeline, from retrieval design to answer generation;
  • developing the ingestion pipeline, including source connectors, chunking, embeddings and incremental refresh;
  • implementing security trimming and ACL propagation;
  • setting up agent orchestration, prompt templates and guardrails with Python and LangChain;
  • configuring evaluation and tracing with offline evaluation datasets, retrieval metrics, answer-quality metrics, and end-to-end tracing of requests and agent steps;
  • creating the Terraform, Helm and Azure DevOps artefacts required to deploy and operate the service on Azure and AKS;
  • improving observability and cost control, including monitoring of latency, token usage, run cost and quality regressions after model or prompt changes;
  • supporting hypercare and early production through incident analysis, tuning, runbooks, documentation and handover to the engineer responsible for the run phase.

📝 Your profile

You have solid experience as a Senior AI Engineer in environments where Azure-based AI services move from design into production.

Essential expertise for this role includes:

  • senior-level experience with Python, RAG applications, LLMs, Azure OpenAI Service, Azure Kubernetes Service (AKS), Azure DevOps and Terraform;
  • hands-on knowledge of Azure services used in AI delivery, deployment and operations;
  • experience building and operating AI services with a strong focus on maintainability, evaluation and production readiness;
  • good understanding of retrieval patterns, embeddings, prompt design, guardrails and observability for AI workloads.

The following skills are also relevant:

  • experience with LangChain;
  • knowledge of vector databases;
  • familiarity with Helm, MLflow, Databricks, Azure AI Search, Azure API Management and Azure AI Content Safety.

You communicate professionally in Dutch or French, and you can work effectively in English.

💼 Offer

You will be part of a growing Belgian SME where initiative and personal development are encouraged. We will provide you with an enjoyable work environment with fun colleagues. We will work out a career plan with you, with attention and a budget for extra education/certification. You can count on an attractive salary, supplemented with extra-legal benefits, including a company car.

(Freelance is also possible)

Originally posted on Himalayas

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About the job

Posted on
Oct 10, 2026
Job type
Contract
Location
BelgiumOn-site

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