This role offers a unique combination of engineering depth and innovation within a technology company. You will help AI solutions evolve from prototype to scalable production environments with visible impact on core processes such as claims management, fraud, and underwriting. You will have the opportunity to further develop MLOps/AIOps and provide technical direction for agentic solutions, contributing to the foundation upon which AI will be rolled out in the coming years.
You will have autonomy to co-shape technical standards and best practices. As an AI Engineer, you will be part of the AI team and report to the Team Lead. You will work in an Agile team to bring AI solutions reliably, scalably, and securely into production.
What you will do.
- Combine in-depth expertise in AIOps/MLOps with technical leadership around agentic automation.
- Work independently and serve as the technical point of contact for the team.
- Translate, together with the business, a concrete problem into a solution that runs in production and is used.
- Guide data scientists in deploying models to production environments and ensure AI solutions meet high quality, security, and governance requirements.
- Design and build reliable data and inference pipelines, implement CI/CD processes, and set up observability via logging, monitoring, alerts, and drift detection.
- Collaborate with internal Security, Risk & Compliance departments to develop AI solutions compliant by design.
- Take a leading role in the development of agentic solutions, from proof of value to production design and build.
- Build performant solutions that securely integrate with internal systems via APIs, tool use/function calling, RAG, and robust orchestration patterns.
- Define evaluation and testing frameworks, perform code reviews, and help embed best practices within the team.
- Work AI-first and contribute to reusable components and standards.
- Advise Product Owner and Domain Product Manager on architectural choices, risks, feasibility, and sequencing.
- Challenge designs from external delivery partners and prevent isolated PoCs and shadow AI.
- Contribute to AI governance, documentation, standards, and the further development of AI literacy within the organization, in collaboration with architecture, IT, data scientists, and external delivery partners.
Profile
- At least 6 years of experience in software or data engineering, of which at least 3 years as an AI/ML Engineer, MLOps Engineer, or in a similar role, with AI solutions you have brought into production yourself.
- Experience as a technical lead with contributions to architectural choices, performing code reviews, and coaching colleagues.
- Strong knowledge of AIOps/MLOps, CI/CD, Azure DevOps, Git, Docker, containers, Kubernetes, and Infrastructure as Code (Terraform).
- Experience with model registries, feature stores, experiment tracking, monitoring, alerting, and data and inference pipelines.
- Strong Python knowledge and solid software engineering practices (testing, clean code).
- Experience with Azure ML, Azure OpenAI, AI Foundry, Azure AI Search, Fabric, Jfrog/ACR, and AKS.
- Knowledge of agentic frameworks, RAG, Copilot Studio, dspy, tool use/function calling, and semantic caching.
- Knowledge of security, governance, RBAC, secrets management, data privacy, and the EU AI Act is a strong asset.
- Knowledge of Microsoft Fabric & DB / Vector DB.
- Strong communication skills, coaching attitude, pragmatic and results-oriented; you dare to make decisions and clearly explain technical choices to non-technical colleagues.
- Insurance knowledge is a plus.
- Languages: Dutch and English, with basic knowledge of French.
Expectations.
- Bring AI from experimentation to production and make a difference in core processes.
- Take the lead in developing secure, performant, and scalable agentic solutions.
- Collaborate with data scientists, architects, and IT experts on the next generation of AI solutions.
How to apply
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