AI Engineer - GenAI & Customer Service

GeekSoft Consulting; Utrecht; On-site; EUR 70,000 - 110,000; Full time

Job summary

GeekSoft Consulting is seeking an AI Data & Evaluation Engineer to join a Scrum team in Utrecht. You will prepare, structure, enrich, and validate enterprise data for AI knowledge bases and AI chatbots; build Databricks pipelines for structured and unstructured data; and ensure data quality for AI assistants.

You will deploy cloud infrastructure with IaC and contribute to evaluating chatbot scenarios. The role emphasizes automated testing, CI/CD, and an ownership mindset within an Agile

Qualifications

• Experience preparing, structuring, enriching, and validating enterprise data for AI knowledge bases and AI chatbots.
• Building and maintaining Databricks data pipelines for structured and unstructured data.
• Prepare, clean, transform, and enrich source data to improve data quality for AI assistants.
• Develop and maintain evaluation datasets for realistic conversations, edge cases, and multi-step workflows.
• Apply evaluation frameworks to test chatbots across single-turn, multi-turn, simulation, and agentic scenarios.
• Implement automated testing, monitoring, and quality gates for data, prompts, models, retrieval, and orchestration.

Responsibilities

• Help design, build and improve the client’s online platform.
• Research, suggest and implement new technology solutions following best practices/standards.
• Ensure resiliency and availability of different products.
• Be a productive member of the team.

Skills

Python

Data engineering

Automated testing

Agile development

Critical thinking

Ownership

Communication skills

Customer-focused

English fluency

Education

Relevant HBO or university degree

Tools

Azure

Databricks

DevOps

CI/CD

Infrastructure as Code

Bicep

Job description

GeekSoft Consulting | Fixed Term Employment

Utrecht, Netherlands

• Help design, build and continuously improve the clients online platform.
• Research, suggest and implement new technology solutions following best practices/standards.
• Take responsibility for the resiliency and availability of different products.
• Be a productive member of the team.

Requirements

• AI Data & Evaluation Engineer to work within a Scrum team, preparing, structuring, enriching, and validating enterprise data for AI knowledge bases and AI chatbots.
• Build and maintain Databricks data pipelines to process structured and unstructured data for AI knowledge bases.
• Prepare, clean, transform, and enrich source data to improve the quality and reliability of information used by AI assistants.
• Develop and maintain evaluation datasets covering realistic conversations, complex scenarios, edge cases, and multi-step workflows.
• Apply evaluation frameworks to test advanced chatbots across single-turn, multi-turn, simulation-based, and agentic scenarios.
• 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.
• Analyze evaluation results and translate findings into improvements across knowledge, retrieval, prompts, tools, and application logic.
• Strong proficiency in Python, 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 with chatbot evaluation, including multi-turn, simulated, and agentic interactions.
• Familiarity with Context Engineering, Agentic AI, Function Calling, retrieval strategies, and tool use.
• Strong engineering and data-quality mindset with an affinity for Agile development.
• Strong critical thinking, ownership, accountability, and problem-solving skills.
• Excellent communication skills and a customer-focused approach.
• Relevant HBO or university degree and fluency in English.
• A challenging, innovating environment.
• Opportunities for learning where needed.