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AI Native Software Engineering

Pubblicato il 15-08-2026 - Accenture in Latina

Role Description
Kick-start your engineering career at Accenture as an Early Talent AI Native Engineer. This is an entry-level role designed for recent graduates and early-career engineers with strong software engineering foundations, high learning agility, and demonstrated AI curiosity. You will be hired with a clear hire-to-train model and developed into a client-facing, full-stack, AI-native engineer embedded directly in delivery teams.
As an Early Talent AI Native Engineer, you will work across the full software development lifecycle building and evolving custom applications, platforms, and APIs while learning to leverage cloud, DevOps, and AI tools to accelerate delivery. You will develop your ability to translate business needs into scalable, production-ready solutions alongside experienced engineers and architects.
We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with structured AI certification pathways, vendor learning access inside Anthropic, OpenAI, Microsoft,



and Google, and a clear development track toward AI Native and Forward Deployed Engineering as you grow.
Key Responsibilities
- Collaborate with engineers, architects, and product teams to design, build, test, and deploy custom applications and services
- Develop API-driven and platform-based solutions across front-end and back-end using your primary language (Python, Java, or TypeScript)
- Work in Agile delivery models (Scrum, Lean, XP) — contributing reliably to sprint cycles and communicating progress clearly
- Use AI coding assistants daily as a standard part of delivery — actively, frequently, and with demonstrable impact on your productivity and output quality
- Apply AI across the software delivery lifecycle: AI-generated tests, AI-assisted debugging, AI-accelerated code review, and prompt engineering for development tasks
- Validate AI-generated outputs — check for errors, lim

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