携程AI Operation Supervisor HK NP(MJ022654)

Job Description We are seeking a highly motivated and creative AI Solution to join our Customer Service Center team. The focus of this position is to improve the quality and efficiency of our customer service operations by designing and building dialogue bots for text using Natural Language Understanding techniques. The ideal candidate will have a strong understanding of NLP and LLM principles, experience in crafting effective prompts, and a passion for pushing the boundaries of AI-powered communication and problem-solving. LLM and NLP Application in Customer Service: Design, develop, and iterate on prompts for various LLM applications within the customer service center, including conversational AI, content generation, and summarization. Experiment with prompt formats, styles, and techniques to optimize LLM performance and output quality. Analyze LLM-generated responses, identify biases or limitations, and implement mitigation strategies to enhance customer satisfaction and service performance. Operational Excellence: Identify and propose innovative projects that leverage LLMs to solve complex problems or explore new capabilities in customer service. Performance Analysis: Analyze the content of customer interactions to generate self-service rate analysis reports, explaining why customers transfer to agents and what can be done to improve these indicators. Generate regular chat-bot performance reports and continuously improve the algorithm model accuracy, customer satisfaction, and service performance of the chat-bot. Team Collaboration: Work closely with relevant function teams to deliver an integrated workflow of demand negotiations, standard creations, and project implementations. Share knowledge and best practices with the team, mentor junior AI operation peer, and contribute to a collaborative learning environment.

Ø Complete AI relevant training courses provided by AI team and get the AI trainer certification Ø Design customer-robot interaction by reviewing our knowledge base, including Q&A maintenance to guarantee business coverage of the knowledgebase. Standard answer script writing and optimization natively in specific language and keep answers in line with updated business procedure. Optimize the content of the answers, business logic configurations and answer display according to customer’s needs and real time booking status. Ø Improve the customer intention recognition accuracy of the chat-bot by performing corpus annotation in a high-quality manner, which will be used for AI model training. Ø Identify the issues in the customer-robot interactions, prudently analyze the relevant data and generate regular chat-bot performance reports, and continuously improve the algorithm model accuracy, customer satisfaction, and service performance of the chat-bot. Ø Analyze the agent sessions by looking into the conversation between customer-robot and customer – advisor, along with customer behavior during the service recorded in system, then find out the reason of transfer to agent, and come up with suggestions for chat-bot optimization. Ø Collaborate with relevant function teams to deliver an integrated workflow of demand negotiations, standard creations and project implementations.

LLM Application in Customer Service: Design, develop, and iterate on prompts for various LLM applications within the customer service center, including conversational AI, content generation, and summarization. Experiment with prompt formats, styles, and techniques to optimize LLM performance and output quality. Analyze LLM-generated responses, identify biases or limitations, and implement mitigation strategies to enhance customer satisfaction and service performance. Operational Excellence: Identify and propose innovative projects that leverage LLMs to solve complex problems or explore new capabilities in customer service. Conduct research, experiment with cutting-edge techniques, and develop prototypes for potential products or services. Collaborate with data scientists, machine learning engineers, and other stakeholders to integrate prompts and research findings into the broader AI/ML pipeline. Performance Analysis: Analyze the content of customer interactions to generate self-service rate analysis reports, explaining why customers transfer to agents and what can be done to improve these indicators. Generate regular chat-bot performance reports and continuously improve the algorithm model accuracy, customer satisfaction, and service performance of the chat-bot. Team Collaboration: Work closely with relevant function teams to deliver an integrated workflow of demand negotiations, standard creations, and project implementations. Share knowledge and best practices with the team, mentor junior AI operation peer, and contribute to a collaborative learning environment.

In this role, you will be leading day-to-day operations to ensure organizational delivery of high quality annotated data from the group of Team Leads you support. You will effectively lead team performance by developing Team Leads, and other Senior Annotation roles, through individual coaching, team meetings, mentor sessions, participating in interviewing and hiring, data analysis, and collaboration with other Data Operations sites. You’ll also assist in the development of tools and reports needed analyze and run the business, including workflow optimization, workforce management, and developing more efficient ways of working. You will help determine staffing requirements and participate in interviewing and hiring. The role is an office based position. Additionally, some specific supervisor shifts require certain hours to be present on campus, and can span any hours of operations.