Senior Agentic AI Engineer

Senior Agentic AI Engineer – LLM / RAG / Multi-Agent Systems Location: Amsterdam, Netherlands Working Model: Hybrid Contract: Long-term opportunity Experience: 8+ years Language: English About the Role We are looking for an experienced Senior Agentic AI Engineer to design, build and deploy enterprise-grade AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and multi-agent systems. You will work on the development of AI-powered automation, intelligent assistants and data-driven decision platforms, taking solutions from initial design through to scalable, secure and production-ready deployment. This is a hands-on engineering role requiring strong Python, Generative AI and cloud engineering expertise, alongside experience building modern AI and data platforms. Key Responsibilities • Design, develop and deploy Agentic AI applications using LLMs, RAG, embeddings and vector databases • Build sophisticated multi-agent AI systems and intelligent workflows • Develop AI-powered assistants, automation solutions and decision-support platforms • Design and optimise RAG pipelines for enterprise use cases • Build and optimise AI workflows using LangChain, LlamaIndex and similar frameworks • Integrate applications with Azure OpenAI and other cloud-based AI services • Design scalable AI and data pipelines across Azure and/or AWS • Work with vector databases and embedding models to support semantic search and retrieval • Develop production-grade solutions using Python and SQL • Implement MLOps practices covering deployment, monitoring, evaluation and retraining • Build and maintain scalable data processing solutions using technologies such as Databricks, Spark and Airflow • Containerise and deploy applications using Docker and Kubernetes • Contribute to CI/CD pipelines and automated deployment processes • Monitor and optimise AI applications for performance, scalability and reliability • Implement appropriate AI security, governance and responsible AI controls • Collaborate closely with software engineers, data engineers, architects and business stakeholders • Translate business requirements into scalable AI-driven technical solutions • Ensure AI platforms and applications are secure, reliable and production-ready Essential Skills & Experience • 8+ years of experience across Software Engineering, Data Engineering, Machine Learning or AI Engineering • Strong hands-on programming experience with Python • Strong SQL skills • Commercial experience designing and developing Generative AI / LLM applications • Hands-on experience with Agentic AI and multi-agent systems • Strong understanding of Retrieval-Augmented Generation (RAG) • Experience working with embeddings and vector databases • Hands-on experience with LangChain, LlamaIndex or comparable AI orchestration frameworks • Experience with Azure OpenAI or similar enterprise LLM services • Strong knowledge of Microsoft Azure and/or AWS • Experience designing scalable AI and data pipelines • Knowledge of Databricks, Apache Spark and Airflow • Experience with Docker and Kubernetes • Strong understanding of CI/CD and DevOps principles • Experience taking AI/ML solutions from development into production environments • Understanding of MLOps, including model deployment, monitoring, evaluation and retraining • Strong understanding of security, governance and reliability requirements for enterprise AI Technology Environment Python | SQL | Agentic AI | Generative AI | LLMs | RAG | Multi-Agent Systems | LangChain | LlamaIndex | Azure OpenAI | Embeddings | Vector Databases | Microsoft Azure | AWS | Databricks | Spark | Airflow | Docker | Kubernetes | CI/CD | MLOps Nice to Have • Experience delivering AI solutions within Financial Services or Capital Markets • Experience designing enterprise-scale AI platforms • Strong understanding of AI evaluation and observability • Experience with prompt engineering and LLM optimisation • Knowledge of AI security and governance frameworks • Experience integrating LLM solutions with existing enterprise systems and data platforms