Senior Full Stack AI Engineer (Generative AI & Agents)

Discover Your Impact as a Senior Full Stack AI Engineer (Generative AI & Agents) at Rabobank

This is what we offer you

• Thirteenth month's salary and 8% holiday allowance
• 10% Employee Benefit Budget
• EUR 1,400 development budget per year
• Hybrid working: balance between home and office work (possible for most roles)
• A pension, for which you can set the maximum amount of your personal contribution

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.

You & your role

We’re building GenAI solutions that are as impactful for our customers as they are exciting for us to create — and we need your help. As a Senior GenAI Engineer, you’ll be part of a multi-disciplinary team with end-to-end ownership of your work: from data ingestion to deployment and monitoring.

You’ll design and deploy scalable GenAI systems, automate relentlessly across the development lifecycle and collaborate across teams to drive innovation. You’ll apply your technical expertise to ensure performance, reliability and real-world impact.

Practical examples

• You are part of an empowered self-performing team. Your voice is heard and you contribute directly to the product, or service, your squad is responsible for.
• Design and build responsible and cost effective GenAI solutions for up to 9.5 million Rabobank customers.
• Convert a use-case specific code base to re-usable building blocks used by 100+ tech teams.
• Pair-program with members of your squad and across other Squads within Rabobank to solve critical or complex problems.

Work on yourself & the world around you

At Rabobank, your development and that of society go hand in hand. That’s why we invest in you and work together for a better world. We sum it up in one sentence: at Rabobank, you work on yourself & the world around you.

You will see this reflected in your personal development budget, our hybrid working environment, and a healthy work-life balance. You can work on banking matters for our private and business customers, as well as on societal issues such as food and energy transitions.

You and your talent

Technical Leadership:

• Design and implement scalable GenAI solutions using Azure services (e.g., Azure OpenAI, Azure ML, AKS, Azure Functions, API Gateway) and moving to portability and cloud-agnostic, resilience etc over time.
• Develop and maintain CI/CD pipelines using GitHub, Azure DevOps, Terraform, Bicep and Kong.
• Build Python-based microservices and automation tools to support GenAI workflows, infrastructure provisioning and agent-based orchestration.
• Integrate and manage GenAI products to support complex multi-step workflows and decision-making processes.
• Ensure security, compliance and performance optimization across GenAI workloads.

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.

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.