Neo Enterprise Engineering Manager

Capgemini is an AI-powered global business and technology transformation partner with nearly 60 years of heritage, employing over 420,000 team members in more than 50 countries. The Group reported 2025 global revenues of 0.5 billion. Capgemini delivers end-to-end services and solutions leveraging capabilities across strategy, technology, design, engineering, and business operations.

• Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science or a related field
• Experience leading engineering teams in frontend, full-stack, or AI product environments
• Strong expertise in modern frontend technologies such as React, Angular, or Vue
• Solid understanding of backend development including APIs, JavaScript/TypeScript, Node.js, Express or NestJS
• Practical knowledge of AI/ML product concepts including LLMs, RAG, embeddings, vector search, and prompt engineering
• Experience working with Python in AI/LLM contexts including model integration, orchestration, data processing, and evaluation
• Experience delivering enterprise-grade applications with strong focus on security, observability, and performance
• Familiarity with cloud platforms, preferably GCP (e.g. Cloud Run, BigQuery, Firestore, Cloud Storage, Vertex AI, Apigee)
• Strong collaboration and stakeholder management skills, with experience working across Product, UX, Engineering, and Architecture in agile environments

• Lead and develop a team of frontend, full-stack, and AI product engineers to deliver high-quality product experiences
• Drive delivery of user-facing AI capabilities including chat, agents, knowledge retrieval, prompt flows, and feedback loops
• Ensure scalable, performant, and maintainable frontend architecture using modern frameworks (e.g. React)
• Guide teams on AI-ready implementation patterns such as RAG flows, prompt orchestration, streaming, and evaluation
• Collaborate closely with Product, UX/UI, AI/ML, Backend, Security, Cloud, and QA teams
• Translate business and product needs into clear engineering plans, milestones, and standards
• Establish best practices across code quality, CI/CD, testing, observability, accessibility, and performance
• Drive continuous improvement using user feedback, adoption data, and AI performance insights

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. Individuals are evaluated based on qualifications and performance, not personal characteristics.