Dev Ops Engineer C

AI Engineer – GenAI Assistants within Customer Service The role

As an AI Engineer, you will prepare enterprise data and knowledge for advanced AI assistants and evaluate their quality across single-turn, multi-turn, simulated, and agentic scenarios. You will help ensure that assistants provide accurate, grounded, and reliable support to advisors.

What you’ll do

• Collaborate within a Scrum team to prepare, structure, enrich, and validate enterprise data for AI knowledge bases and chatbots.
• Build and maintain Databricks data pipelines for structured and unstructured data.
• Prepare, clean, transform, and enrich source data to improve the quality and reliability of information used by AI assistants.
• Apply evaluation frameworks to test chatbots in single-turn, multi-turn, simulation-based, and agentic scenarios.
• 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 to knowledge, retrieval, prompts, tools, and application logic.

What you bring

• A relevant HBO or university degree.
• Fluency in English.
• A strong engineering and data-quality mindset, with an affinity for Agile development.
• A proactive, hands-on approach to complex AI-quality and cloud-engineering challenges.
• Strong critical-thinking skills, ownership, and accountability for production-ready solutions.
• Excellent communication skills and a customer-centric attitude.

Your skills and experience

• 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 evaluating advanced chatbots, including multi-turn, simulated, and agentic interactions.
• Familiarity with Context Engineering, Agentic AI, Function Calling, retrieval strategies, and tool use.