The team

You will join ING's global Analytics organization, working with Product Leads, Engineers, Data Scientists, and business stakeholders across countries and domains. The team develops intelligent systems using Generative AI, Large Language Models, retrieval technologies, and agentic workflows for highly regulated financial-services environments.

This is a hands-on individual-contributor role for an experienced Data Scientist who wants to broaden their technical influence. You will help teams make sound architectural choices, establish reusable practices, share knowledge, and turn promising ideas into solutions that create measurable business value.

Roles and responsibilities

As a Senior AI/LLM Data Scientist in Agentic AI, you will:

• Design, build, and deploy AI agents and intelligent workflows powered by Large Language Models.
• Develop multi-agent solutions that interact with tools, APIs, databases, workflows, and business applications.
• Create Retrieval-Augmented Generation architectures using vector databases, embeddings, and retrieval-based patterns.
• Build context-aware AI solutions that combine business data, enterprise systems, and Large Language Models.
• Define technical standards, guide architectural decisions, and contribute to reusable Agentic AI practices across ING.
• Establish evaluation, monitoring, governance, reliability, and model-optimization approaches for production AI solutions.
• Collaborate across disciplines and countries, while mentoring Data Scientists and promoting knowledge sharing.

How to succeed

We hire smart people like you for your potential. Our biggest expectation is that you'll stay curious. Keep learning. Take on responsibility.

To be successful in this role, you bring:

• At least five years of experience in Data Science, Machine Learning, NLP, Generative AI, or a related discipline, supported by a relevant degree or equivalent expertise.
• A track record of building and deploying production-grade AI applications, with strong Python skills and production-ready software-engineering practices.
• Hands-on experience with LLM, Generative AI, NLP, or Agentic AI solutions, including modern prompting, evaluation, and model-optimization approaches.
• Practical experience designing RAG systems using vector databases, embeddings, and retrieval-based architectures.
• Experience integrating AI systems with APIs, tools, databases, workflows, and enterprise platforms.
• Clear communication and strong collaboration skills, including the ability to mentor and coach Data Scientists and foster knowledge sharing.

An advantage: experience with LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, Azure AI, OpenAI APIs, Vertex AI, workflow orchestration platforms, fine-tuning, PEFT, or distributed AI architectures.

We value leadership impact and adaptability as much as strict checklist experience. If your background aligns with the core vision of this role, even if you don't tick every single bullet point, we strongly encourage you to apply. Tell us in your application or cover note what unique perspective and track record you'll bring to the team.