Key Skills

Job Description

Everience is an international consulting group delivering AI-augmented digital services and placing people at the heart of the AI revolution. With a presence in Europe, Africa, Asia and America, Everience offers its 4,000-strong workforce the most demanding and stimulating environment in which to transform and develop their skills, learning about new AI-based roles and building their future employability. Through its Symbiotic Academy the group offers a unique hub for training, practical application and exchange where everyone can experiment, learn, and progress in the fields of artificial intelligence and data. In accordance with its core purpose of orchestrating the symbiotic relationship between humans and AI in the workplace, Everience is making the augmented employee the driving force of a “symbiotic age”, where AI enhances talents and opens up new career opportunities. Job Description A client is looking for an AI Engineer to strengthen their Conversational AI teams. The consultant 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, the consultant will help ensure AI 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 AI 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. Qualifications 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. A relevant HBO or university degree and fluency in English. 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. Additional Information All our positions are open to both women and men and are, of course, open to people with disabilities. All our positions are open to both women and men and are, of course, open to people with disabilities.

Core Responsibilities

Prepare, structure, and maintain enterprise data pipelines and knowledge bases for AI assistants, and evaluate chatbots across single-turn, multi-turn, simulated, and agentic scenarios. Analyze evaluation results and improve data, retrieval, prompts, tools, orchestration, and application logic while implementing automated quality controls and managing cloud infrastructure.

Requirements

Requires a relevant HBO or university degree, fluency in English, strong Python skills, and experience in data engineering and automated testing. Candidates should have hands-on experience with Azure, Databricks, DevOps, CI/CD, Infrastructure as Code, enterprise data preparation for AI and RAG, and evaluation of advanced chatbots.