Generative AI Engineer

About the role

AXA Global Business Services is looking for a Generative AI Engineer to design, develop and maintain AI-powered solutions that support business needs across several domains. You will build scalable GenAI applications, implement Retrieval-Augmented Generation (RAG) architectures, integrate Large Language Models (LLMs) into enterprise ecosystems and help improve AI capabilities across the organization. The role works closely with business and technical teams.

Key responsibilities

• Analyze business requirements and turn them into AI-powered solutions.
• Design, develop, test and deploy GenAI applications such as assistants, chatbots, copilots and autonomous agents.
• Implement RAG architectures, including data ingestion, indexing, retrieval and response generation.
• Develop and orchestrate LLM workflows with LangChain, LangGraph, MCP and similar frameworks.
• Integrate AI services with APIs, databases, data platforms and enterprise applications.
• Optimize prompts, retrieval strategies and model interactions, and set up evaluation frameworks for AI performance.
• Ensure AI systems meet security, compliance and responsible AI requirements, and take part in code reviews.
• Produce technical documentation and share knowledge, and contribute to improving AI platforms and processes.

Required profile

• 2 to 7 years of experience in AI, machine learning, data engineering or software engineering roles.
• Proven experience developing and deploying AI-powered applications, including enterprise-scale GenAI solutions.
• Ability to define technical standards, mentor team members and engage with senior stakeholders.
• Experience leading AI transformation initiatives and complex solution architectures.
• Experience in Agile environments and producing technical documentation.

Required skills

• Python and software engineering; hands-on experience with LLMs, RAG, vector databases and prompt engineering.
• LangChain, LangGraph, MCP or equivalent AI orchestration frameworks.
• RAG implementation, semantic and hybrid search, and knowledge management architectures.
• SQL, REST APIs, Git, Docker, CI/CD, and cloud platforms (Azure and/or AWS).
• Responsible AI, security, privacy and compliance awareness.