Conversational AI Engineer

Summary

Join RYZ Labs as a Conversational AI Engineer to lead the development of our AI concierge service. You will design and optimize conversational flows, integrate advanced language models, and ensure seamless user interactions. Your expertise will directly impact user experience, improving accuracy and delivering exceptional results. You will collaborate with the Backend Integration Developer and manage AI-related data, ensuring quality and relevance. Continuous iteration on models and flows based on user insights is key. Maintain comprehensive documentation and communicate effectively within the team and with stakeholders.

Requirements

• Proven expertise in NLP and NLU, with hands-on experience implementing conversational AI systems
• Proficiency in Python, JavaScript, and TypeScript for AI development and integration tasks
• Strong experience working with AWS Lex and deploying AI-driven solutions in cloud environments
• Familiarity with large language models (LLMs) and the latest advances in conversational AI technologies
• Demonstrated ability to manage and organize AI-specific data for optimal performance
• Exceptional written and verbal communication skills, with a keen attention to detail and clarity
• Collaborative mindset with a passion for solving complex challenges and iterating quickly in a fast-paced team setting

Responsibilities

• Lead the selection, configuration, and integration of the AI concierge service or large language models within our platform
• Design and implement robust conversational flows, defining intents, entities, and responses on platforms such as AWS Lex
• Collaborate with the Backend Integration Developer to connect AI-driven conversations with data sources and internal APIs
• Monitor and analyze the performance of conversational AI, identifying areas for improvement in user interactions and accuracy
• Manage data related to AI, including training phrases, conversation logs, and user feedback, ensuring data quality and relevance
• Continuously iterate on models and flows based on user insights and analytics to enhance overall system effectiveness
• Maintain comprehensive documentation and advocate for clear, effective communication within the team and with stakeholders