Data Scientist GENAI

Our clients Agentic AI Centre of Excellence (CoE) is a small, high-impact team that is defining how one of Europe's largest banks can safely put AI agents to work at scale. We operate at the frontier of what's technically possible in a regulated financial environment, which means we constantly balance the tension between moving fast and meeting real institutional constraints. We're looking for data scientists and 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.Who we're looking for You are a builder with hands on experience developing agentic AI systems and AI-powered applications. You have full-stack platform development experience, and know how to turn proofs-of-concepts into deployed production-grade solutions, and you have enough data science fluency to quantitatively assess whether an agent actually performs well, or just appears to. You communicate clearly and with precision, and can translate between engineers, product managers, and business stakeholders. You are pragmatic and assertive when working under institutional constraints. Where resources are limited, and approval chains are long, you find ways to make things work without cutting corners that matter. When priorities shift, you reorient quickly and keep moving. You collaborate effectively with other teams to include Rabobank's requirements on data safety and data protection into a larger Agentic AI solution that meets all regulatory requirements and best practices. Your work will directly influence how millions of customers experience AI-driven banking. 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 ResGen/GenAI workflows, infrastructure provisioning and agent-based orchestration.Integrate and manage GenAI agents (e.g., LangChain, Semantic Kernel) to support complex multi-step workflows and decision-making processes.Ensure security, compliance and performance optimization across ResGen/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 juniors and contribute to a culture of learning and innovation.Required Qualifications:Shipped at least one AI-powered product (ideally an agentic or multi-step AI system) that real users interacted with in production .8+ years of strong hands-on development experience, fluency in Python, and strong Cloud and DevOps practicesPractical experience with agentic AI frameworks (LangGraph, Semantic Kernel, AutoGen or comparable)Excellent communication and stakeholder management skills.Experience mentoring juniors or leading technical teamsExperience working in an Agile environment. Either SCRUM or Kanban