Chatbot & Conversational AI Developer – Hybrid Belgium

Montash; Vlaams-Brabant; Hybride; EUR 83 000 - 138 000; Plein temps

Résumé du poste

Montash is seeking a Bot / Conversational AI Developer in Belgium for a hybrid freelance contract. You will join a Belgian bank's use-case team to design and deliver AI-powered conversations and new functionality for customers through the bank's digital assistant.

You will develop conversational flows across multiple projects, interpret requirements into technical designs, expand the codebase to high quality standards and integrate APIs and backend systems, using LLMs to boost efficiency.

Qualifications

• Must have practical experience with Python and Java (Spring preferred).
• Strong understanding of CI/CD concepts and Git workflows.
• Cloud-native design, RESTful services and microservices.
• Experience with LLMs or generative AI.
• Ability to integrate APIs and backend systems.
• Excellent written and spoken English for technical and non-technical stakeholders.

Responsabilités

• Design and develop conversations so new use-cases can be introduced into the bank's assistant.
• Interpret requirements and translate into technical design and code.
• Uphold and expand the codebase to high quality standards.
• Work on multiple parallel projects while maintaining quality and focus.
• Leverage AI agents to automate tasks and improve development efficiency.
• Integrate APIs and backend systems into conversational experiences.
• Collaborate with Product Owner, Scrum Master and team members.

Connaissances

Python

Java

CI/CD

Git

Cloud-native

LLMs

API integration

English comms

Outils

Docker

Podman

Kubernetes

AWS

Description du poste

Montash is seeking a Bot / Conversational AI Developer in Belgium for a hybrid freelance contract. You will join a Belgian bank's use-case team to design and deliver AI-powered conversations and new functionality for customers through the bank's digital assistant.

You will develop conversational flows across multiple projects, interpret requirements into technical designs, expand the codebase to high quality standards and integrate APIs and backend systems, using LLMs to boost efficiency.