4 days ago
Madrid, SpainSenior
Responsibilities
- Develop AI-powered applications and proofs of concept using frontier AI models, commercial AI services, and open-weight models.
- Design and implement solutions using Large Language Models, Retrieval-Augmented Generation, and Agentic AI patterns.
- Build secure, scalable, production-ready AI solutions aligned with security and governance requirements.
- Evaluate, benchmark, and monitor AI systems for capabilities, limitations, risks, and security implications.
- Build AI agents and agentic workflows using relevant frameworks and emerging AI protocols.
- Develop end-to-end data-to-model-to-deployment pipelines and apply MLOps/LLMOps practices.
- Share knowledge and contribute to AI security capabilities, standards, guidance, and best practices across the organization.
- Collaborate with policy bodies, industry forums, research institutions, and internal stakeholders on AI security and safety.
Requirements
- Master’s degree or PhD in computer science, artificial intelligence, cybersecurity, software engineering, mathematics, physics, or a related field.
- 8+ years of experience in AI engineering, software engineering, machine learning, cybersecurity, or a related discipline.
- Demonstrated experience building and operating production-grade AI solutions at enterprise scale.
- Advanced Python and SQL skills, with experience using PyTorch or TensorFlow; SAS is an advantage.
- Experience with MLOps/LLMOps practices, including model lifecycle management, evaluation, monitoring, observability, and CI/CD.
- Strong software engineering fundamentals, including testing, code quality, software architecture, and distributed systems design.
- Experience with HuggingFace Transformers and PEFT, LangChain or LlamaIndex, vector stores, and designing and optimizing RAG pipelines.
- Experience building AI agents and agentic workflows using frameworks such as LangGraph, CrewAI, AutoGen, or similar.
- Understanding of Model Context Protocol, Agent-to-Agent communication, tool-calling, and multi-agent architectures.
- Familiarity with AI evaluation frameworks, benchmarking, and model observability.
- Strong experience with Google Cloud Platform, including Vertex AI and Workbench, and Azure DevOps, including Git and Pipelines.
- Experience with end-to-end pipelines spanning data, models, and deployment.
- Experience working in Agile/Scrum teams and following a You Build It, You Run It philosophy.
- Knowledge of AI risk governance and a strong interest in cybersecurity, emerging technologies, and responsible AI.
Benefits
- Flexible hybrid work model, with employees determining home and office days together with ING.
- Restaurant card.
- Office facilities including electric mobility solutions, a doctor, hairdresser, gym, and errand-support services.
- Health insurance for the employee and family.
- Life insurance.
- Flexible remuneration options including nursery, transport card, and training aids.
- Transport allowance.
- Pension plan available after one month with ING.
Tech Stack
Categories
About ING
ING is a Dutch multinational bank providing retail, private, and wholesale banking, with strong digital and mobile services for consumers and businesses. Founded in 1991 and headquartered in Amsterdam, it operates across Europe and beyond, earning revenue from interest income, fees, and financial services. ING is a public company with shares traded in New York.