Senior Full Stack AI Engineer (Generative AI & Agents)                 

• Salary: Gross monthly salary between EUR 5,876 and EUR 8,395 (scale 10).
• Extras: a thirteenth month, 8% holiday allowance, and a 10% Employee Benefit Budget.
• Development budget: EUR 1,400 development budget per year for your growth and development.
• Hybrid working: a balance between home and office work (possible for most roles).
• Pension: decide for yourself the amount of your personal contribution.

Or view all our benefits.

Senior Full Stack AI Engineer (Generative AI & Agents)               

Driving AI Forward at RabobankOur Analytics Acceleration Area is growing fast to meet the demand for next-generation AI solutions. As a bank, our customers expect us to stay ahead—and we’re committed to leading the way. That’s why we’re looking for engineers who combine technical excellence with adaptability, collaboration and a strong sense of ownership. These qualities are key to making our cultural shift real and impactful. We’re recruiting the next wave of GenAI changemakers.

Who we’re looking forTenacious engineers—passionate about software engineering, craftsmanship and relentless in their pursuit of impact. You finish what you start, thrive in ambiguity, adapt when priorities shift and persist through technical complexity. Your work will directly influence how millions of customers experience AI-driven banking.

Your mindset mattersAre you an entrepreneurial thinker whose ideas deserve to be heard? In our Area, leadership actively drives innovation and removes roadblocks so you can focus on what matters. We’ve got your back.

What makes this role special

• Work in a culture that values initiative, grit and impact.
• Freedom to experiment, learn and grow—with full leadership support.
• A healthy work-life balance because sustainable performance matters.
• We value curiosity, resilience and the ability to learn fast.

A word of cautionWe’re not just looking for GenAI enthusiasts—we’re looking for exceptional  Engineers & Data Scientists. People who aim for excellence, thrive on solving tough challenges and know how to build from first principles.

If your coding journey started before the rise of GenAI, you’ll feel right at home. We value engineers who understand the fundamentals, who can build & beyond.

We’re building AI‑powered agents that run in production and are used daily by Rabobank engineering teams. As a Senior GenAI Engineer, you’ll play a key role in shaping how these systems are designed, built and scaled.

You’ll take ownership of complex GenAI agent architectures, guide technical decisions, and mentor others in building reliable, fast and user‑centric AI systems.

This is a hands‑on engineering role for someone who combines strong software fundamentals with deep interest in GenAI — and who thrives in ambiguity, experimentation and rapid delivery.

You’ll help set standards for agent design, system integration and developer experience, while continuously pushing for simplicity and impact.

• Designing and building AI agents that automate code reviews, backlog refinement or software delivery workflows
• Turning exploratory GenAI prototypes into robust, reusable building blocks used by dozens of teams
• Define and implement mean to track the value delivered across the SDL by these agents.
• Coaching engineers on effective use of GenAI in software development
• Making architectural trade‑offs between speed, cost, reliability and scalability
• Improving developer experience by embedding GenAI directly into existing tools and platforms

• 36 or 40 hours a week.
• Mostly greenfield, very little legacy work.
• Approx. 43,822 Rabobank colleagues around the world.

Technical Leadership:

·  Design and implement scalable GenAI systems and agent architectures

·  Build production‑ready GenAI services using Azure‑based platforms, with an eye towards portability

·  Lead solution design across APIs, event‑driven systems and AI workflows

·  Evaluate and select appropriate frameworks without over‑reliance on abstractions

·  Ensure performance, security and cost‑effectiveness of GenAI workloads

·  Mentor medior and junior engineers in both engineering fundamentals and GenAI practices

Collaboration & Stakeholder Engagement:

• Collaborate with Data Science, Product and Business teams to translate requirements into technical solutions.
• Collaborate on the design and deployment of AI workflows, including prompt engineering, chaining and memory management.
• Communicate technical concepts effectively to both technical and non-technical stakeholders.
• Act as a trusted advisor on GenAI strategy, infrastructure scalability and operational excellence.

Soft Skills & Leadership Qualities:

• You are relentless in getting things done, you don’t give up, you adapt & find another way to complete your assignment. Lead by example in problem-solving, adaptability & continuous improvement.
• Entrepreneurial - Salesmanship mindset – you see valuable opportunities to pitch your ideas to Leadership, and you have the persistence to adapt your pitch even if you are told “no”.
• Excellent communication skills – able to simplify complex ideas and build trust across teams. Foster collaboration and alignment across engineering and business teams.
• Mentorship mindset – Mentor medior and junior engineers and contribute to a culture of learning and innovation.
• You combine technical depth with strong product intuition. You challenge solutions that are complex but low‑impact, and you are comfortable making decisions with incomplete information — learning quickly through experimentation.

Required Qualifications:

• 5+ years in technical roles (DevOps, Software Engineering, ML Engineering, or Data Science).
• Proven experience deploying AI workloads (preferably Generative AI or agentic systems) in production environments, with a focus on scalability and cost optimization.
• Strong hands-on expertise with Cloud platforms: Azure (preferred) or AWS or GCP, along with DevOps practices and Infrastructure as Code (Terraform/Bicep).
• Proficiency in Python for automation, API development, and AI model integration.
• Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI) and AI workflow orchestration.
• Understanding of vector databases and RAG patterns for retrieval-augmented generation.
• Experience with containerization and orchestration (Docker, AKS/Kubernetes).
• Knowledge of API gateways and service mesh technologies (e.g., Kong, Istio).
• Security and observability awareness: best practices for monitoring, compliance, and reliability in AI systems.
• Excellent communication skills with the ability to mentor and lead technical teams.
• Agile experience (SCRUM or Kanban) and strong collaboration across cross-functional teams.

• Questions about working at Rabobank or the process? Raphaël Drenthel,  IT Recruiter via Raphael.Drenthel@rabobank.nl
• After submitting your CV and motivation, we’ll respond as soon as possible
• Answers to frequently asked questions can be found at rabobank.jobs/nl/veelgestelde-vragen.
• A reliability screening is part of the procedure.
• We respect your privacy.

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