AXA México operates a mid-market insurance operation across health, life, auto, and property lines, serving over 5,000 employees from Ciudad de México. The tech stack reveals a data-driven, ML-forward organization: Python, R, PyTorch, TensorFlow, scikit-learn, plus LangChain and LlamaIndex signal active AI/LLM integration, while fraud detection and cost containment dominate the pain-point list. Sales roles represent the largest hiring cohort, but the adoption of RAG and OpenAI APIs alongside internal ML tooling suggests engineering is building analytical and risk-assessment capabilities to support sales and underwriting.
AXA México is a full-service insurance carrier offering health, life, auto, and property coverage to Mexican consumers. Founded in 2008, the company operates from Mexico City with a workforce of 5,001–10,000 employees. Current priorities center on sales growth, campaign management, customer satisfaction, and fraud mitigation. Active projects span commercial campaign execution, productivity dashboards, identity and access management implementation, and control-tracking infrastructure. The organization is actively hiring across sales, operations, and insurance underwriting roles.
Core: Python, Java, SQL, R, PyTorch, TensorFlow. ML/AI: scikit-learn, LangChain, LlamaIndex, Hugging Face, OpenAI API, MLOps, RAG. Cloud: AWS, Azure. BI/productivity: Power BI, Jira, Microsoft 365.
Fraud detection, cost containment, budget compliance, customer satisfaction, meeting sales targets, and portfolio volatility. Projects focus on dashboards for productivity, campaign coordination, and IAM implementation.
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