IT services division scaling data, AI, and cloud infrastructure for insurance group
G2S is the internal technology engine for Groupama, a 12-million-member insurance mutual, operating 1,500 engineers across a Java/Scala/Spark stack paired with legacy mainframe systems (z/OS, COBOL). Current hiring velocity is accelerating, heavily weighted toward senior engineers (32 of 78 open roles) and data roles (18 positions), signaling a push toward real-time data architecture and AI model deployment — reinforced by active projects in CI/CD pipelines for LLM agents, AI demonstrators, and datalab platform evolution.
Notable leadership hires: Tech lead
G2S is an internal IT and digital transformation organization operating as a dedicated subsidiary of Groupama. The group services all IT functions for Groupama's business lines, plus real-estate operations and procurement across roughly ten French locations. The technology remit spans data engineering, cybersecurity, AI/ML, cloud migration, and legacy system modernization. Internally, G2S operates with a focus on collective success and mutualist principles (solidarity, responsibility, proximity), with remote-work flexibility for its workforce.
G2S runs a hybrid stack: Java, Scala, Spark, Hadoop for modern data systems; PostgreSQL, MongoDB, Oracle for databases; Kafka, Apache Camel for event streaming; and legacy z/OS, COBOL for mainframe systems. DevOps tooling includes OpenShift, Kubernetes, Docker, GitLab CI/CD, ServiceNow, and Jira.
Active projects include CI/CD pipeline implementation for AI models and LLM agents, AI demonstrators and prototypes, datalab and AI platform evolution, Copilot Studio conversational assistants, and legacy system modernization. Data-centric real-time architecture and regression test industrialization are documented operational priorities.
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GROUPAMA - G2S's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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