AI Engineer – Data Engineering and AI Evaluation
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Sommige details van deze opdracht zijn niet publiek beschikbaar.
Over de opdracht
This assignment focuses on preparing enterprise data and evaluating AI assistants that support personalized financial choices and provide reliable information to advisors. The AI Engineer works within a collaborative, agile team to develop data foundations and quality evaluation for conversational AI in a customer-service environment.
Responsibilities
The role involves preparing, structuring, enriching, and validating data for AI knowledge bases and chatbots. This includes building and maintaining data pipelines for structured and unstructured information, and improving source data quality. The engineer applies evaluation frameworks across single-turn, multi-turn, simulated, and agentic interactions, and creates datasets covering realistic conversations, complex cases, edge cases, and multi-step workflows.
Responsibilities also include implementing automated testing, monitoring, and quality gates for changes to data, prompts, models, retrieval, and orchestration. The engineer analyses evaluation results and turns findings into improvements to knowledge, retrieval, prompts, tools, and application logic. The role includes deploying and managing cloud infrastructure through Infrastructure as Code and CI/CD pipelines.
Working arrangements
The role is hybrid, with an expectation of one day per week onsite at a regional office. Mondays are team office days; arrangements for the rest of the week are coordinated within the team, between working from home and the office.
Eisen
- A relevant HBO or university degree.
- Fluency in English.
- Strong proficiency in Python.
- Experience with data engineering and automated testing.
- Hands-on experience with a cloud platform, a data engineering platform, DevOps, CI/CD, and Infrastructure as Code; experience with a declarative cloud infrastructure language is preferred.
- 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, simulation-based, and agentic interactions.
- Familiarity with Context Engineering, Agentic AI, Function Calling, retrieval strategies, and tool use.