AI Native Software Engineering

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, limitations, and hallucinations; develop sound judgment about when AI output is reliable and when human verification is required
  
• Contribute to proofs of concept, technical documentation, and solution development alongside senior engineers
  
• Engage in client-facing environments and learn to communicate technical concepts clearly to non-technical stakeholders
  
• Develop your understanding of how agentic systems work — how agents are orchestrated, how LLMs are called, and how software connects to AI pipelines — through on-the-job exposure and active self-development

Compensation at Accenture varies depending on a wide array of factors including but not limited to role, level, seniority, responsibility, skillset, and level of experience. For this position, the job level is under the C3 National Collective Bargaining Agreement. The gross annual salary range is between 24,000 and 34,600 EUR.

Basic Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field
  
• Foundational programming experience in at least one primary language: Python, Java, TypeScript, or Node.js
  
• Basic understanding of web technologies including JavaScript, HTML, and CSS
  
• Academic projects, internships, or personal projects in software development that demonstrate you can build and ship working code
  
• Understanding of Agile delivery fundamentals
  
• Active and frequent use of AI tools in day-to-day study or work — successful candidates can demonstrate practical, everyday examples of how they leverage AI to solve problems, accelerate learning, and improve their output
  
• Sound judgment when using AI: ability to validate outputs, understand limitations, and show curiosity about how AI is reshaping modern software engineering
  
• Demonstrated curiosity about agentic AI — evidence of self-directed exploration through personal projects, side builds, online courses, or experimentation with tools like LangChain, LangGraph, AutoGen, or equivalent; we are looking for inclination and initiative, not production experience

Preferred Skills & Exposure

• Some exposure to LLM APIs in any context (personal projects, coursework, or work)
  
• API and service-oriented architecture
  
• Databases — SQL or NoSQL
  
• Cloud platforms (AWS, Azure, or GCP) and DevOps concepts
  
• Frontend frameworks such as React or Angular
  
• Containers (Docker) and CI/CD pipeline basics