Dev Ops Engineer C

AI Engineer — GenAI Assistants (Customer Service)

Role overview: Prepare enterprise data and knowledge for advanced AI assistants and apply evaluation frameworks across single-turn, multi-turn, simulated, and agentic scenarios to ensure assistants provide accurate, grounded, and reliable support to advisors.

Key responsibilities

• Collaborate within a scrum team to prepare, structure, enrich, and validate enterprise data for AI knowledge bases and chatbots.

• Build and maintain data pipelines in Databricks to process structured and unstructured data for AI knowledge bases.

• Apply evaluation frameworks to test advanced chatbots across single-turn, multi-turn, simulation-based, and agentic scenarios.

• Prepare, clean, transform, and enrich source data to improve the quality and reliability of information used by AI assistants.

• Create and maintain evaluation datasets covering realistic conversations, complex cases, edge cases, and multi-step workflows.

• Implement automated testing, monitoring, and quality gates for changes to data, prompts, models, retrieval, and orchestration.

• Deploy and manage cloud infrastructure using Infrastructure as Code, particularly Azure Bicep and CI/CD pipelines.

• Analyse evaluation results and translate findings into improvements across knowledge, retrieval, prompts, tools, and application logic.

Your profile

• Mindset: Strong engineering and data-quality mindset with an affinity for Agile development.

• Approach: Proactive, hands-on problem solver for complex AI-quality and cloud-engineering challenges.

• Attributes: Strong critical thinking, ownership, and accountability for production-ready solutions.

• Communication: Excellent communication skills and a customer-centric attitude.

• Education & language: Relevant HBO or university degree and fluency in English.

Required skills

• 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.

• Familiarity with Context Engineering, Agentic AI, Function Calling, retrieval strategies, and tool use.