Genai Agentic System

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/77ysqa

Experteer Overview

In this role you will lead the development of autonomous agents and their reasoning capabilities within complex workflows. You will design architectures where collaborative AI agents use external tools and coordinate non-linear tasks, shaping advanced decision‑making systems. You’ll work with cross‑functional teams to deliver scalable, innovative AI solutions aligned with Reply’s digital services focus. This is an opportunity to influence multi‑agent approaches and practical GenAI applications in a consulting and systems integration context. You will join a culture that values curiosity, collaboration, and continuous learning to drive transformational outcomes.

Retribuzione / Benefits

- Design and implement multi-agent architectures enabling collaboration among AI agents
- Develop advanced orchestration for complex, non-linear decision processes
- Integrate external tools and systems to enhance agent capabilities
- Collaborate with cross‑functional teams to deliver scalable AI solutions




- Contribute to shaping the strategy and execution of autonomous agent projects

Responsabilità

- Academic background in computer‑related engineering or science fields
- Hands‑on experience with Generative AI models and libraries
- Familiarity with Large Language Models ecosystem and architectures such as VAE, GAN, or diffusion models
- Proficiency in Python, JavaScript, TypeScript, or Rust
- Solid foundation in Machine Learning/Deep Learning frameworks
- Innovative mindset and willingness to learn in evolving environments
- Strong collaboration and communication skills in multidisciplinary teams

Requisiti fondamentali

- structured career path
- tailored career development
- focus on AI and digital solutions
- inclusive work environment (as part of company policy)
- opportunity to work on advanced AI initiatives
- support for cross-disciplinary collaboration

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Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/77ysqa