AI Developer

About the role

Société Générale Global Solution Centre (SG GSC) Morocco, part of the Société Générale group, is hiring an AI Developer in Casablanca. You will design, build and deploy AI-powered applications and workflow automation solutions that support business transformation and operational efficiency, working with enterprise applications, cloud services and diverse data sources. You will collaborate with business, data, technology and architecture teams across the full development lifecycle.

Key responsibilities

• Design, develop, test and deploy AI-powered applications, intelligent tools and workflow automation solutions.
• Integrate enterprise applications with AI services via REST APIs, Model Context Protocol (MCP), event-driven architectures and workflow orchestration platforms.
• Work with structured, semi-structured and unstructured data sources to build scalable AI solutions.
• Build data-integration components linking AI applications with data warehouses, data lakes, analytics platforms and vector databases.
• Build and maintain CI/CD pipelines and apply DevOps practices throughout the AI application lifecycle.
• Deploy and operate AI solutions on Microsoft Azure in line with enterprise architecture, security and development standards.
• Optimise AI workflows for reliability, scalability, observability, performance and cost efficiency.
• Implement testing, monitoring, logging and technical documentation, and collaborate with stakeholders to support adoption.
• Contribute to code reviews, knowledge sharing and the improvement of development standards and reusable components.

Required profile

• Junior level (1 to 3 years of experience).
• Strong analytical and problem-solving skills, able to turn business requirements into reliable technical solutions.
• Collaborative, delivery-focused approach with clear communication and sound documentation.

Required skills

• Python; working knowledge of .NET/C# for enterprise applications and integrations.
• REST APIs, MCP components and event-driven or orchestrated workflows.
• Git, CI/CD pipelines and DevOps practices.
• Relational, document and vector databases; data platforms such as data warehouses, data lakes, Databricks or Snowflake.
• Familiarity with Microsoft Azure and Azure AI Foundry.
• Understanding of cloud architecture, application security, observability, scalability and cost optimisation.