We’re seeking an experienced AI-Native Engineer (.NET) - someone for whom AI isn’t just a tool, but a way of thinking. You’ll solve problems AI-first and integrate AI seamlessly throughout the software development lifecycle. office remote European Union Requirements

5+ years of development experience in .NET Background in C#, .NET Core, and ASP.NET Core Experience with databases (SQL or NoSQL), ORM frameworks Good knowledge and hands‑on skills in patterns and practices 1+ years of proven experience implementing AI Software Development Life Cycle Experience in prompt engineering and model integration Working knowledge of assessing, monitoring, deploying, and continuously enhancing AI solutions English skills should be sufficient for taking part in conversations on the technical aspects of projects Responsibilities

Design, develop, and deploy AI-driven solutions leveraging .NET technologies Lead the implementation of business‑critical features powered by AI Engage across every stage of the AI software development lifecycle (solution architecture, model integration,



prompt engineering, evaluation, deployment, and ongoing enhancement) Build and maintain REST APIs and backend services Maintain high‑quality code via code reviewsand commitment to software engineering best practices Keep current with trends in .NET and AI technologies We offer

Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota Competitive compensation that depends on your qualification and skills Career development system with clear skill qualifications Versátil working hours aligned to your schedule Options to work remotely Corporate medical insurance covering services of private and public medical centers English courses online Corporate parties and events for employees and their children Internal conferences, workshops and meetups for learning and experience sharing 5 days of paid sick leave per year with no obligation to submit a sick‑leave certificate

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📌 AI-Native Engineer (.NET) (Madrid)
🏢 Itransition Group
📍 Madrid