Artificial Intelligence Engineer

This is a hands-on delivery role where your technical decisions directly influence client outcomes.

• Translate business problems into deployable AI solutions so clients can reduce costs, improve decision-making, or unlock new capabilities
• Design and implement machine learning models that move beyond experimentation and deliver reliable performance in live environments
• Build Generative AI applications (LLMs, RAG pipelines, agents) that automate workflows and enhance productivity at scale
• Own projects from discovery to deployment, giving you full visibility across architecture, modelling, and operational performance
• Deploy models into cloud environments with monitoring in place so solutions remain stable, measurable, and continuously improving
• Work directly with stakeholders to shape practical AI strategies rather than theoretical roadmaps

Your work won’t sit in isolation, it will be implemented, measured, and iterated on in real-world settings., * You will work across varied industries, broadening your technical exposure

• You will gain hands-on experience with both traditional ML and modern Generative AI applications
• You will develop architectural thinking, positioning yourself for Technical Lead or Solution Architect progression
• You will operate in an environment that prioritises delivery quality and long-term impact
• Salary up to €70,000 plus company car and benefits
• Hybrid working model (2 days office / 3 days remote)

If you’re looking for a role where your AI expertise translates directly into deployed solutions and visible client impact, this is worth a conversation.

• Strong grounding in machine learning and data science principles
• Commercial Python experience with modern ML frameworks
• Experience with, or clear exposure to, Generative AI concepts such as embeddings, RAG, and prompt optimisation
• Ability to write clean, maintainable code suitable for production systems
• Experience deploying solutions in cloud environments
• Comfort working across the full lifecycle - from raw data through to monitored production systems
• Clear communication skills for working in client-facing or cross-functional settings
• Fluency in Dutch (spoken and written) to work effectively with local clients and stakeholders

Additional Experience That Adds Value

• Exposure to MLOps practices such as CI/CD pipelines, experiment tracking, and monitoring
• Familiarity with LLM orchestration frameworks
• Experience delivering solutions in enterprise or regulated environments
• Consultancy or stakeholder-facing project experience