Tech Riders

AI Engineer

• Work across the entire AI project lifecycle: ideation, experimentation, scaling, and industrialization
• Define and promote AI technical standards and best practices relating to code quality, performance, security, maintainability, API integration, and cloud deployment
• Provide AI technical expertise and challenge architecture and modeling decisions
• Select and oversee the use of commercial, open-source, and cloud-based LLMs
• Guide the implementation of effective RAG techniques
• Ensure the performance, compliance, security, adoption, and business operation of AI models
• Ensure the scalability, robustness, and interoperability of models with existing systems
• Optimize performance and resource consumption
• Contribute to defining environmental KPIs related to the use of AI models, including energy efficiency, carbon footprint, and GPU resource utilization
• Analyze KPI trends and propose optimization initiatives to improve energy efficiency and reduce environmental impact
• Maintain continuous awareness of advances in AI and propose innovative technical improvements
• Support cross-functional teams of Developers, Data Scientists, and Architects in applying development and industrialization best practices
• Work with the software vendor and operations provider to deploy and integrate AI models into the client’s cloud and on-premise infrastructures
• Propose and oversee technical and methodological improvements to optimize the integration and deployment of AI models

AI Tech Lead