Amsterdam, Netherlands | Posted on 02/02/2026
We are seeking a highly skilled Generative AI Engineer to design, build, and deploy enterprise-grade AI solutions leveraging Large Language Models (LLMs), multi-modal AI, and scalable data platforms. The role focuses on developing advanced Generative AI use cases while ensuring robust ML Ops practices, data governance, and secure cloud-native deployments on Microsoft Azure.
Key Responsibilities- Design, develop, and deploy Generative AI solutions for NLP, Computer Vision, and multi-modal applications.
- Research, evaluate, and integrate state-of-the-art LLMs, including fine‑tuning and prompt engineering for enterprise use cases.
- Build and optimize large‑scale data pipelines using Azure Databricks and Apache Spark.
- Develop and maintain ML Ops pipelines for model training, deployment, monitoring, versioning, and lifecycle management.
- Collaborate closely with data scientists, cloud architects, product owners, and business stakeholders to deliver AI‑driven solutions.
- Ensure adherence to Responsible AI, data governance, security, and compliance standards.
- Optimize model performance, scalability, and cost efficiency in cloud environments.
- Contribute to architectural decisions and best practices for AI and data platforms.
- Strong proficiency in Python and ML/AI frameworks such as TensorFlow, PyTorch, and Hugging Face.
- Deep expertise in Generative AI, Large Language Models (LLMs), prompt engineering, and model fine‑tuning.
- Hands‑on experience with Azure Databricks, Apache Spark, and distributed data processing.
- Solid understanding of Azure cloud architecture, including designing and deploying cloud‑native AI solutions.
- Strong experience with CI/CD pipelines for ML workflows.
- Hands‑on knowledge of ML Ops, model monitoring, and version control.
- Experience with containerization and orchestration tools such as Docker and Kubernetes.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
€70000 - €90000 monthly
