opción
Hogar Lista de Prompts de IA AI Redactor de ofertas para startup tecnológica

Redactor de ofertas para startup tecnológica

{:__('collect %s',Redactor de ofertas para startup tecnológica)}
AI
32

Redacte una oferta de empleo adecuada para un desarrollador backend junior en una startup de 30 empleados de 2 años de antigüedad, ajustada a plataformas de empleo chinas.

Contenido del prompt Copiar Copiar

Write a 500-word-max recruitment copy for a junior backend developer position at a domestic Chinese ToB SaaS startup that is less than two years old and has 30 total employees. The copy needs a lively and friendly tone, highlight flat management and flexible growth space, and fit the release format of Lagou.com.

Copiar Copiar

Redacte una oferta de empleo de máximo 500 palabras para un puesto de desarrollador backend junior en una startup SaaS B2B china con menos de dos años de antigüedad y 30 empleados en total. La oferta debe tener un tono animado y amigable, resaltar la gestión plana y el espacio de crecimiento flexible, y ajustarse al formato de publicación de Lagou.com.

Copiar Copiar
comentario (0)
0/300

Recomendación

Clasificación de Tickets EC
Please analyze the following user customer service conversation records from an e-commerce platform, determine the business category based on the content such as logistics inquiry, return or exchange application, product quality complaint, or account anomaly, extract key information like order number, problem description, and user sentiment, and finally output a structured ticket classification result for subsequent manual or automated processing.
Clasificación de Tickets EC
Please analyze the content of the following user customer service tickets from an e-commerce platform, determine which category their core request belongs to based on the conversation context (logistics inquiry, return/exchange application, product quality complaint, or price consultation), and output the corresponding category label along with a brief reason.
Clasificación de Tickets
Analyze the following e-commerce support ticket content, identify its core issue type, including logistics delay, product damage, refund request, or inquiry, and route it to the logistics, quality inspection, or finance department based on preset rules. Extract key entities such as order number, product name, and user sentiment, and finally output a structured classification result and suggested handling plan to ensure accurate classification and compliance with business standards.
Clasificador de tickets de comercio electrónico
Act as an intelligent customer service system for an e-commerce platform. Receive raw user inquiry or complaint text, analyze its core intent, and classify it into specific business scenarios such as logistics inquiry, product quality issue, return or exchange request, or price dispute. Output a standardized classification label along with a brief handling suggestion to ensure the customer service team can respond quickly and accurately.
Clasificación de Tickets EC
Please analyze the following e-commerce customer inquiry ticket content, automatically categorize it into one of the four categories: 'Logistics Inquiry', 'Return/Exchange Application', 'Product Quality Complaint', or 'Other Inquiry' based on business semantics, and briefly explain the basis for classification, ensuring that the classification results conform to actual business scenarios and are logically clear.
Clasificador de Tickets de E-commerce
Act as an e-commerce support specialist to analyze the provided customer ticket text, identifying whether the core issue falls under logistics delay, product damage, return/exchange request, or price dispute. Extract key entities such as order ID, product name, and user sentiment, then output a structured classification result with suggested handling priority, ensuring accuracy and compliance with company service standards.
OR