Artificial Intelligence Engineer

Webologix Ltd/ INC

Utrecht

Sur place

EUR 90 000 - 125 000

Plein temps

Il y a 3 heures
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Résumé du poste

Webologix Ltd/ INC is seeking an AI Engineer - RAG Platform in the Netherlands (Utrecht) to continuously improve our internal Retrieval-Augmented Generation platform. You will work at the intersection of information retrieval, data science and software engineering to boost answer quality and production performance.

You’ll join a team of engineers responsible for production-grade improvements, measuring outcomes with robust evaluation and telemetry, and translating insights into scalable

Qualifications

  • Master's degree or equivalent in a relevant field is required.
  • At least 3 years of experience in machine learning, applied AI or data science.
  • Proven track record improving production-grade RAG systems or retrieval-based AI solutions.
  • Experience designing evaluation methodologies and quality metrics.
  • Strong ability to translate analyses into automated production solutions.

Responsabilités

  • Improve retrieval performance, answer quality and user experience through experimentation and optimization.
  • Build evaluation and measurement capabilities for RAG.
  • Develop automated frameworks that measure RAG quality and identify regressions.
  • Turn insights into production outcomes and scalable engineering solutions.
  • Translate data analysis and experimentation results into measurable business value.
  • Collaborate with software, platform, data science and product teams for continuous improvement.
  • Balance scientific rigor with engineering excellence and data-driven decision making.

Connaissances

RAG
Python
Databricks
Evaluation frameworks for GenAI
Prompt optimization
Data pipelines
CI/CD practices

Formation

Master's degree or equivalent in Data Science/AI/CS/Math/Stats

Outils

Databricks

Description du poste

  • Want to improve one of Client's most strategic AI platforms through data-driven experimentation and measurable model improvements?
You & your role
  • As an AI Engineer - RAG Platform, you are responsible for continuously improving the quality, accuracy and effectiveness of Client's internal Retrieval-Augmented Generation (RAG) platform.
  • You work at the intersection of Information Retrieval, Data Science and Software Engineering. Rather than building AI applications or platform infrastructure, your primary responsibility is improving the performance of the RAG system itself.
  • The RAG platform serves thousands of users across Client and acts as a foundation for multiple AI-powered products. Your focus is understanding where and why the system underperforms, designing experiments to validate improvements and translating insights into measurable production outcomes.
  • You contribute across the entire improvement lifecycle, from failure analysis and hypothesis generation to evaluation, implementation and monitoring. You leverage user feedback, retrieval metrics, evaluation datasets and production telemetry to continuously increase answer quality and user trust.
  • This role is designed for a highly analytical and hands-on specialist who wants to deepen their expertise in retrieval systems, evaluation methodologies and applied AI rather than moving towards people management or generic product development.
  • You will work closely with Software Engineers, Platform Engineers, Data Scientists and Product Managers, while acting as the driving force behind the continuous improvement of Client's RAG capabilities.
Key responsibilities
  • Improve retrieval performance, answer quality and overall user experience through experimentation, analysis and optimization.
  • Build evaluation and measurement capabilities
  • Develop automated frameworks that measure RAG quality, identify regressions and provide actionable insights for future improvements.
  • Turn insights into production outcomes
  • Translate data analysis and experimentation results into scalable, maintainable engineering solutions that deliver measurable business value.
  • Together we achieve more than alone
  • The RAG platform is not a research project. It is a production product that must continuously improve.
  • You will join a team of experienced engineers who are building and operating critical AI capabilities within Client. Success in this role comes from combining scientific rigor with engineering excellence. We value people who challenge assumptions, validate ideas through data and continuously raise the quality bar.
  • We are looking for someone who enjoys solving hard problems and is driven by measurable outcomes. Someone who is equally comfortable discussing statistical significance, retrieval metrics and system architecture.
  • You take ownership of results rather than activities. You are naturally curious, analytical and passionate about improving complex systems.
Mandatory skills
  • Retrieval-Augmented Generation (RAG);
  • Python;
  • Databricks;
  • Evaluation frameworks for GenAI systems;
  • Prompt optimization;
  • Data pipelines and workflow automation;
  • CI/CD practices;
Nice to have
  • Experience with fine-tuning language models;
  • Experience with ranking and retrieval systems;
  • Experience with AI observability and monitoring;
  • Experience working with large-scale production AI platforms;
  • Knowledge of synthetic evaluation datasets and benchmark creation.
Knowledge and experience
  • Master's degree or equivalent academic level in Data Science, Artificial Intelligence, Computer Science, Mathematics, Statistics or a related field;
  • At least 3 years of relevant experience in machine learning, applied AI or data science;
  • Demonstrable experience improving production-grade RAG systems or advanced retrieval-based AI solutions;
  • Experience designing evaluation methodologies and quality metrics;
  • Strong track record of converting analyses into automated production solutions;
  • Experience working with large datasets and complex distributed environments;
  • Ability to communicate findings and recommendations to both technical and non-technical stakeholders;

Proficiency in English, both written and spoken

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