Senior AI Engineer for RAG Solutions on Azure and Kubernetes

h3Senior AI Engineer for RAG Solutions on Azure and Kubernetes (Employed or freelance) /h3 pJob Openings Senior AI Engineer for RAG Solutions on Azure and Kubernetes (Employed or freelance) /p h3About the job Senior AI Engineer for RAG Solutions on Azure and Kubernetes (Employed or freelance) /h3 h3Tasks and responsibilities /h3 pThis role focuses on the build and hypercare phases of complex AI services used by both employees and customers across the organization. /p pYou 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. /p pThe 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. /p h3What you will deliver /h3 pYour activities may differ by project, but typically include: /p ul libuilding the end-to-end RAG pipeline, from retrieval design to answer generation; /li lideveloping the ingestion pipeline, including source connectors, chunking, embeddings and incremental refresh; /li liimplementing security trimming and ACL propagation; /li lisetting up agent orchestration, prompt templates and guardrails with Python and LangChain; /li liconfiguring evaluation and tracing with offline evaluation datasets, retrieval metrics, answer-quality metrics, and end-to-end tracing of requests and agent steps; /li licreating the Terraform, Helm and Azure DevOps artefacts required to deploy and operate the service on Azure and AKS; /li liimproving observability and cost control, including monitoring of latency, token usage, run cost and quality regressions after model or prompt changes; /li lisupporting hypercare and early production through incident analysis, tuning, runbooks, documentation and handover to the engineer responsible for the run phase. /li /ul pYou have solid experience as a Senior AI Engineer in environments where Azure-based AI services move from design into production. /p pEssential expertise for this role includes: /p ul lisenior-level experience with Python, RAG applications, LLMs, Azure OpenAI Service, Azure Kubernetes Service (AKS), Azure DevOps and Terraform; /li lihands-on knowledge of Azure services used in AI delivery, deployment and operations; /li liexperience building and operating AI services with a strong focus on maintainability, evaluation and production readiness; /li ligood understanding of retrieval patterns, embeddings, prompt design, guardrails and observability for AI workloads. /li /ul pThe following skills are also relevant: /p ul liexperience with LangChain; /li liknowledge of vector databases; /li lifamiliarity with Helm, MLflow, Databricks, Azure AI Search, Azure API Management and Azure AI Content Safety. /li /ul pYou communicate professionally in Dutch or French, and you can work effectively in English. /p pYou 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.br/(Freelance is also possible) /p