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Salary: Gross monthly salary between EUR 5,030 and EUR 7,183 (scale 09) for a 36-hour work week.
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Extras: a thirteenth month, 8% holiday allowance, and a 10% Employee Benefit Budget.
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Development budget: EUR 1,400 development budget per year for your growth and development.
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Hybrid working: a balance between home and office work (possible for most roles).
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Pension: decide for yourself the amount of your personal contribution.
Or view all our benefits.
Banking is evolving toward a model where conversational AI becomes the primary interface between customers and the bank. Instead of navigating screens, customers increasingly interact through natural conversations, powered by AI agents that understand intent, maintain context, and guide them toward the right financial decisions.
Within the Growth Accelerator 0–30, we build conversational AI capabilities and financial specific agents (e.g. for budgeting, onboarding, or financial insights) that integrate into the bank’s central AI agent, which orchestrates end-to-end customer interactions.
As an Applied AI Engineer, you are responsible to gain the relevant insights to improve how these agents behave, learn, and deliver value. You work on the intelligence layer of the system: designing how models interpret inputs, generate outputs, and evolve based on real-world usage.
You operate at the intersection of data, machine learning, and product development, ensuring that AI-driven experiences are not only functional, but also accurate, reliable, explainable, and continuously improving.
Together with business analysts, backend engineers, and designers, you translate conversational journeys and business goals into effective model behaviour, experimentation strategies, and data-driven improvements.
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Designing prompting strategies and reasoning patterns that improve the quality of conversational AI responses.
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Building evaluation frameworks that measure AI agent performance on accuracy, relevance, safety, and consistency.
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Using conversation logs, intent data, and feedback signals to improve AI agents after launch.
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36-40 hours per week.
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You work within Growth Accelerator 0–30, focused on digital experiences for young people.
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Over 48,000 Rabobank colleagues worldwide.
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Improve LLM-driven conversational behaviour by designing prompts, reasoning patterns, feedback loops, and response quality improvements.
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Build evaluation pipelines that measure AI agent performance and help teams make clear, data-driven product decisions.
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Collaborate with business analysts, backend engineers, and designers to translate journeys, intents, and decision logic into reliable AI behaviour.
You help Rabobank build conversational AI that is accurate, explainable, responsible, and ready to improve through real customer use. Your work has a direct impact on trust, customer experience, and the future of digital banking.
We believe in the power of differences. By combining people's differences, we become an even better bank. We are curious about what you will bring to our team at Growth Accelerator 0–30.
The teams of Growth Accelerator 0–30 build innovative digital customer experiences in the Rabo App for young people. Collaboration is our way of working; as one data-minded team within Rabobank. You work with proposition managers, journey experts, UX/UI designers, data analysts, developers, architects, business analysts, product owners, and other specialists to create impact from customer question to launch and continuous improvement.
For us, your development and that of society go hand in hand. That is why we invest in you and work together to create a better world. At Rabobank, you work on yourself and the world around you simultaneously.
This is reflected in your personal development budget, our hybrid work environment, and a healthy work-life balance. You also contribute to digital banking experiences that help young people make better financial choices. In this way, you work on innovation, customer trust, and Growing a better world together.
At Rabobank, we are building a culture where everyone feels welcome. We value differences and use them to collaborate better and make stronger decisions. We do this step by step, with attention to what is already going well and where we can keep improving.
By being open to different perspectives, we create an environment where colleagues feel heard. That helps us build an organisation where people enjoy working and where we truly understand and serve our customers.
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Experience in applied machine learning, data science, or AI engineering
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Proven experience working with LLMs or NLP systems in real-world applications.
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Experience with Python and ML frameworks.
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Hands-on experience with LLMs, including prompting, evaluation, and optimisation techniques.
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Designing and implementing evaluation pipelines, metrics, and benchmarking approaches.
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Experience with experiment design and A/B testing in AI-driven systems.
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Working with data pipelines, feature engineering, and dataset creation.
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Understanding of conversational AI concepts, such as intent detection, context handling, and agent orchestration.
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Knowledge of responsible AI practices, including bias mitigation, explainability, and safety guardrails.
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Strong analytical mindset with the ability to translate ambiguous problems into measurable improvements.
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Experience working in cross-functional teams, bridging product, engineering, and data.
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A strong sense of ownership: proactive, curious, and driven to continuously improve systems.
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A customer- and outcome-focused mindset, understanding that model quality directly impacts trust and experience.
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If you are invited for an interview, Bo, our virtual assistant, will contact you via SMS and email to schedule the interviews.
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You can find answers to frequently asked questions here.
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Assessments can be part of the application process.
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A reliability assessment is part of the procedure. We respect your privacy.
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