Dev Ops Engineer C

AI Engineer for GenAI Assistants within Customer Service. We believe customer interactions are evolving toward AI agents that actively support personalized financial choices. These agents depend on high-quality enterprise data and knowledge to provide accurate, grounded, and reliable support. Preparing this information and systematically evaluating the quality of AI assistants are essential to creating valuable customer-service solutions. That is why we are looking for an AI Engineer to strengthen our Conversational AI teams.

You will focus on preparing enterprise data and knowledge for advanced AI assistants and applying evaluation frameworks across single-turn, multi-turn, simulated, and agentic scenarios. In this role, you will help ensure that our assistants provide accurate, grounded, and reliable support to advisors. You will work in a hybrid setup, ideally spending one day a week onsite in Utrecht, collaborating closely with teams to implement new conversational and AI concepts.

On Mondays, our department works from the office. For the rest of the week, we coordinate among ourselves whether we work from home or the office. The Digital & Customer Interaction Tribe aims to deliver an excellent customer experience, regardless of how the customer contacts Rabobank. Core values of our area include fun, collaboration, proactivity, and problem-solving. Your main focus will be on collaborating within a scrum team to prepare, structure, enrich, and validate enterprise data for AI knowledge bases and AI chatbots; building and maintaining data pipelines in Databricks to process structured and unstructured data for AI knowledge bases; applying evaluation frameworks to test advanced chatbots across single-turn, multi-turn, simulation-based, and agentic scenarios; preparing, cleaning, transforming, and enriching source data to improve the quality and reliability of information used by AI assistants; creating and maintaining evaluation datasets covering realistic conversations, complex cases, edge cases, and multi-step workflows; implementing automated testing, monitoring, and quality gates for changes to data, prompts, models, retrieval, and orchestration; deploying and managing cloud infrastructure using Infrastructure as Code, particularly Azure Bicep and CI/CD pipelines; and analysing evaluation results and translating findings into improvements across knowledge, retrieval, prompts, tools, and application logic.

Your talent includes a strong engineering and data-quality mindset, with an affinity for Agile development; a proactive, hands-on approach to solving complex AI-quality and cloud-engineering challenges; strong critical thinking, ownership, and accountability for production-ready solutions; excellent communication skills and a customer-centric attitude; and a relevant HBO or university degree and fluency in English. Your skillset includes strong proficiency in Python and experience with data engineering and automated testing; hands-on experience with Azure, Databricks, DevOps, CI/CD, and Infrastructure as Code, preferably Bicep; experience building data pipelines and preparing structured and unstructured enterprise data for AI knowledge bases and RAG applications; experience applying evaluation methods to advanced chatbots, including multi-turn, simulated, and agentic interactions; and familiarity with Context Engineering, Agentic AI, Function Calling, retrieval strategies, and tool use.