NTT DATA Europe & LatamRemote
AI Engineer (AI-Native Development & Claude-based Systems)
United States of America
Full Time
2 weeks ago
Visa Sponsor
Key skills
Backend EngineeringPlatform EngineeringInsurance DomainInsurance PlatformsInsurance Business ProcessesInsurance Core SystemsClaude Large Language ModelPrompt EngineeringAPI DesignMicroservices ArchitectureEvent-driven SystemsIntegration-based SystemsAILarge Language ModelsClaude
About this role
NTT DATA Europe & Latam is moving towards an AI‑native delivery model where small, highly skilled teams are augmented by AI agents. As an AI Engineer, you will play a key role in building and running the technical backbone that enables this new way of working.
Responsibilities:
- 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
Requirements:
- 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