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Descripción De La Posición

About the Role

Join Accenture’s AI & Data team to build and integrate production-grade applications powered by Large Language Models (LLMs) and enterprise services. In this role, you’ll shape end-to-end solutions—from user experience to APIs and platform operations—helping clients accelerate innovation, improve performance, and scale AI responsibly across the business.

Key Responsibilities

  • Design, develop, and integrate full stack applications that leverage LLMs and AI agent frameworks
  • Build and maintain secure, scalable APIs and backend services that connect AI capabilities with enterprise systems
  • Collaborate with cross-functional stakeholders (product, data, engineering, security, and operations) to deliver high-impact solutions
  • Implement DevOps practices to automate deployment, monitoring, and reliability for AI-enabled applications
  • Conduct thorough testing, debugging, and performance tuning to ensure robust, efficient releases
  • Provide technical leadership and advisory input across multiple teams; drive decisions and reusable patterns where applicable
  • Stay current with advances in LLMs, tooling, and software engineering to continuously improve delivery practices
  • Mentor junior engineers and contribute to a culture of knowledge sharing and continuous learning

    Requisitos

    Required Qualifications

    • Master proficiency in Large Language Models, including application integration patterns and optimization considerations
    • Expert proficiency in Digital Full Stack Development (front-end and server-side)
    • Advanced proficiency in DevOps practices (CI/CD, observability, environment automation, release management)
    • Advanced proficiency in Node.js-based front-end development and modern JavaScript/TypeScript practices
    • Experience building AI-enabled applications using agentic patterns and integrating with enterprise services
    • Strong stakeholder management skills with the ability to influence and communicate across technical/non-technical audiences
    • Bachelor’s Degree in a relevant field (Computer Science, Engineering, or similar)

    Preferred Qualifications

    • Experience with AI orchestration frameworks, prompt/response evaluation, and safety-by-design implementation
    • Familiarity with containerized deployments and cloud-native application architecture
    • Exposure to performance engineering for AI workloads and API scalability patterns

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