Senior Data Scientist (Agentic AI)

Location: CDR, Amsterdam, Netherlands

Company

ING's global Analytics organization develops intelligent systems using Generative AI, Large Language Models, retrieval technologies, and agentic workflows for highly regulated financial-services environments.

What you will do

• 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 enterprise applications.
• Create Retrieval-Augmented Generation architectures using vector databases, embeddings, and retrieval-based patterns.
• Build context-aware AI solutions combining business data, enterprise systems, and Large Language Models.
• Define technical standards, guide architectural decisions, and establish reusable Agentic AI practices.
• Develop evaluation, monitoring, governance, reliability, and model-optimization approaches for production AI solutions while mentoring Data Scientists.

Requirements

• 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.
• Experience building and deploying production-grade AI applications with strong Python and production-ready software-engineering practices.
• Hands-on experience with LLM, Generative AI, NLP, or Agentic AI solutions, including prompting, evaluation, and model optimization.
• Practical experience designing RAG systems with vector databases, embeddings, and retrieval-based architectures.
• Experience integrating AI systems with APIs, tools, databases, workflows, and enterprise platforms.
• Strong communication and collaboration skills, including mentoring and coaching Data Scientists.

Nice to have

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

Culture & Benefits

• Collaboration with Product Leads, Engineers, Data Scientists, and business stakeholders across countries and domains.
• Opportunity to broaden technical influence through architectural guidance and reusable practices.
• Culture focused on curiosity, continuous learning, responsibility, adaptability, and knowledge sharing.
• Hands-on individual-contributor role with leadership impact and mentoring responsibilities.