Senior Data Engineer, AI

We are looking for a Senior Data Engineer with AI expertise to join our driven team. You will work on an exciting project with our client from the insurance sector, focusing on bridging the gap between data science experimentation and enterprise-grade production systems. The role involves transforming AI models and experiments into scalable, reliable and well-governed solutions that integrate seamlessly into business workflows. You will collaborate closely with data scientists, actuaries and business stakeholders to ensure AI solutions are robust, observable and aligned with governance, reliability and cost-efficiency requirements. Responsibilities Design and implement AI workflows combining models, prompts, enterprise data, tools and business logic Develop and maintain prompt engineering strategies, including versioning, testing and optimization Implement orchestration layers for multi-step reasoning, decisioning and action execution Integrate AI capabilities into enterprise systems, APIs and user interfaces Apply guardrails to ensure safe, explainable and compliant AI behavior Build and maintain production-grade AI deployment pipelines Ensure reliability, scalability, latency optimization and cost efficiency of AI services Implement monitoring and observability for AI systems, including usage, performance and drift Establish change control, versioning, rollback and release management practices Collaborate with data scientists and business experts to validate model behavior and outputs Requirements 3+ years of experience in data engineering or AI engineering roles Strong knowledge of MLOps practices and tools Proficiency in Machine Learning concepts and model lifecycle management Advanced programming skills in Python Hands-on experience with Gen AI solutions development and prompt engineering Solid understanding of SQL and data manipulation techniques Experience integrating AI capabilities into enterprise systems and APIs Familiarity with monitoring, observability and governance for AI systems Ability to work in large enterprise data ecosystems Strong problem-solving and communication skills Proficient communication skills in English (B2 level or higher) Nice to have Knowledge of AI governance and data quality Experience with Apache Spark, PySpark and big data tools Familiarity with Natural Language Processing and LLMs Understanding of retrieval-augmented generation techniques Exposure to (Re)Insurance IT or Palantir platform