AYANA Hospitality is one of Indonesia’s leading hotel management companies. We pride ourselves on being an early adopter of large language models (LLMs) in the hospitality industry, where we leverage generative AI across our guest services and internal operations. Our goal is to use AI’s powerful reasoning capabilities to enhance the guest experience and support our teams in delivering world-class hospitality.
As a conversational AI engineer, you will be responsible for the following:
- Development: Design, develop, and deploy conversational AI applications, such as chatbots and voice assistants, to assist guests and internal teams with inquiries, reservations, and personalized recommendations.
- System Integration: Integrate AI solutions with existing hotel systems, including reservation software, CRM tools, and property management systems (like Opera).
- Collaboration: Work closely with guest experience, F&B, marketing, and operations teams to identify high-impact opportunities for AI-driven enhancements.
- R&D: Experiment with new models, prompt-engineering techniques, and tooling to maintain a competitive edge in AI innovation.
- Monitoring: Track and analyze the performance of AI-driven applications, using user feedback and data analytics to optimize accuracy, efficiency, and user satisfaction.
- Data Security and Compliance: Ensure the security and privacy of guest data is in compliance with relevant regulations and industry best practices.
- Training and Support: Provide technical support and training to internal teams on AI solutions, ensuring they understand system capabilities and maintenance requirements.
Requirements
- Exceptional English proficiency for prompt engineering and effective collaboration with both technical and non-technical stakeholders.
- Practical experience building generative AI solutions (e.g., chatbots, recommendation engines) using OpenAI APIs or open-source LLMs.
- Demonstrated ability to craft prompts and iterate on them to optimize model outputs.
- Competence in Python for developing AI-driven applications.
- Familiarity with conversational AI frameworks (e.g., LangChain, LlamaIndex) and basic DevOps or cloud tooling (AWS, GCP, Azure) for smooth production deployments.
- Working knowledge of MLOps best practices, including monitoring, retraining, and version control.
- Awareness of data security and privacy standards (GDPR, PDPA, etc.) to ensure compliant handling of guest information.