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# AI Engineer (AI-Native Development & Claude-based Systems)

- **Company:** NTT DATA
- **Location:** Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Architectural Patterns, Static Program Analysis, Code Generation, Software Tools, Software Engineering, Software Systems, Systems Integration, Large Language Models, Prompt Engineering, Codebase, Api Design, Microservices
- **Published:** August 1, 2026
- **Apply:** https://www.jobleads.com/es/job/e72669d4175412b73faeb1c97140539d2

## About the Role

* 5+ years of professional experience in software engineering, backend, or platform engineering roles
 * Strong software engineering background with hands-on experience in modern architectures
 * Experience in the insurance domain, with exposure to insurance platforms, business processes, or core systems (e.g. policies, claims, billing, underwriting, integrations)
 * Familiarity with AI-native engineering practices, such as agent-based or orchestration-driven approaches (e.g. Gastown-style concepts)
 * Hands-on experience with Claude or similar large language models, including:

 * Using AI tools directly within an IDE or development workflow
 * Writing effective prompts for code analysis, code generation, and iterative refinement

Solid understanding of modern engineering patterns, including:

 * API design and integration
 * Microservices architectures
 * Event-driven and integration-based systems

Experience working with existing, non-trivial codebases and enabling AI-driven analysis on top of them

Practical understanding of prompt engineering as an engineering tool, not just experimentation

A mindset focused on production quality, repeatability, and maintainability rather than demos

Very good command of English (spoken and written), suitable for working in an international, client-facing environment

## Description

* Implement and maintain the AI backbone that supports end-to-end delivery
 * Configure, train, and orchestrate AI models and agents working directly on existing codebases
 * Enable automated gap analysis, requirement refinement, and specification generation using AI
 * Integrate AI capabilities into real-world software systems, not isolated PoCs
 * Ensure AI-driven outputs are robust, scalable, and accurate enough for enterprise use
 * Continuously improve prompts, workflows, and agent coordination to increase quality and consistency
 * Work closely with the Intent Engineer to iterate on outputs and ensure alignment with business intent
 * Support a shift from traditional requirement creation to AI-assisted, exploration-driven delivery


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- [Why your codebase lies to AI?](https://www.wearedevelopers.com/videos/100281-why-your-codebase-lies-to-ai)
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