Medior Full Stack AI Engineer (Generative AI & Agents)

Driving AI Forward at Rabobank

Our 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 for

Tenacious 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 matters

Are 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 caution

We’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.

About the role

As a Medior Full Stack AI Engineer (Generative AI & Agents), you’ll help build production‑grade GenAI agents that meaningfully improve how Rabobank engineers work.

As a Medior GenAI Engineer, you’ll work in a multidisciplinary team with end to end ownership of AI powered products, from rapid prototyping to production rollout. You’ll focus on building, integrating and iterating on GenAI agents that automate real engineering workflows, such as code generation, backlog support or DevOps event handling.

This role requires a strong software engineering foundation, curiosity for GenAI, and the ability to turn abstract ideas into working systems quickly. You’ll learn how to design agentic workflows, work close to users, and balance speed with robustness — supported by senior engineers who value experimentation and continuous learning.

Practical examples

• You are part of an empowered, self performing team where your input directly shapes the GenAI products and services your squad is responsible for.
• Design and build GenAI powered agents that support engineering teams, such as backlog assistants, code generation tools or workflow automation.
• Rapidly prototype new ideas and proofs‑of‑concept and help evolve them into stable, production‑ready solutions.
• Integrate GenAI capabilities with existing platforms, APIs and event‑driven systems used across the organisation.
• Improve and extend previously built GenAI components so they can be reused by multiple teams.
• Pairprogram with colleagues to solve complex problems and continuously improve engineering quality.
• Implement tools to measure the value delivered by this tooling.

What you’ll do in practice

• Design, build and iterate on GenAI driven agent systems, from prototype to production
• Rapidly prototype working solutions (often within hours or days) to validate ideas
• Build and maintain Python based services that integrate GenAI into internal platforms
• Connect agents to APIs, event systems and developer tooling
• Improve agent quality through a combination of software and prompt iteration, evaluation and user feedback
• Collaborate closely with Product Owners, engineers and users to ensure real adoption

About the team

Within Rabobank, Analytics Acceleration is an ambitious area that aims to mix in a healthy dose of experience, innovation and creativity to develop innovative products and services. We focus on fast learning, delivering value quickly and being more efficient. As a team, you work on clear goals and continuously see the results of your (team) efforts.

You and your talent

Technical Ownership:

• Solid software engineering fundamentals and the ability to reason about systems
• Hands‑on experience working with Generative AI APIs or agent‑style solutions
• Proficiency in Python and willingness to work across the stack when needed
• Comfort working in cloud‑based environments (Azure preferred)
• Curiosity to explore new frameworks, SDKs and interaction patterns
• A practical mindset: you prefer a usable first version over a perfect design

Stakeholder Management:

• Collaborate with cross-functional teams including Data Science, Product, and Business to translate requirements into technical solutions.
• Communicate technical concepts clearly to non-technical stakeholders and influence decision-making.
• Act as a trusted advisor for GenAI strategy and infrastructure scalability.

Soft Skills & Leadership Qualities:

• You are “relentless” in getting things done, you don’t give up, you adapt and find another way to complete your assignment.
• 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.
• Mentorship mindset – passionate about helping the Junior colleagues grow and succeed.

Required Qualifications:

• 2–4 years in technical roles (DevOps, Software Engineering, ML Engineering, or Data Science).
• Hands-on experience deploying AI workloads (preferably Generative AI or agentic systems) in development or staging environments.
• Practical experience with Cloud platforms: Azure (preferred) or AWS or GCP, and Infrastructure as Code (Terraform/Bicep).
• Proficiency in Python for automation and API integration.
• Basic familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI) and AI workflow orchestration concepts.
• Understanding of vector databases and RAG patterns at a conceptual level.
• Experience with containerization (Docker) and exposure to orchestration tools (AKS/Kubernetes).
• Knowledge of API development and integration; exposure to API gateways is a plus.
• Awareness of security and monitoring practices for cloud and AI systems.
• Strong communication skills and ability to collaborate effectively within Agile teams (SCRUM or Kanban).