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Raccoon AI

Enterprise AI solutions for customer service

Full-Stack Engineer - AI Customer Service Platform

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeTaipei City, TaiwanNo salary listedHybrid

About the Job

Requirements

  • At least 4 years of software engineering development experience.
  • At least 2 years of experience developing AI-related products, LLM applications, AI agents, AI workflows, or AI backends.
  • Be proficient in Ruby on Rails and able to independently develop and maintain applications, backend APIs, and data models, or be proficient in Python with experience in AI backend, data processing, or LLM application development.
  • Have backend system design ability to design clear, stable, and maintainable APIs and service architectures.
  • Have practical experience integrating third-party APIs and internal systems or implementing asynchronous data-processing workflows.
  • Be able to understand product requirements and translate them into appropriate engineering designs, development tasks, and delivery plans.
  • Value code quality, readability, testing, error handling, and system stability.
  • Be highly interested in AI development, LLM applications, and using AI to solve practical problems, and be willing to explore new tools, frameworks, and implementation approaches.

Responsibilities

  • Develop and maintain application features, backend APIs, and data models for the Raccoon AI customer service platform.
  • Work with PMs to break product requirements into implementable, testable, and maintainable engineering tasks.
  • Build and integrate AI backends, including LLM calls, prompt flows, AI agents, knowledge retrieval, tool calling, and response-generation workflows.
  • Develop and maintain customer-service conversation flows, including AI responses, handoff to human agents, conversation-state management, message records, and administrative features.
  • Integrate external services, internal systems, and third-party APIs, such as e-commerce platforms, CRM systems, order systems, product databases, customer-service systems, and communication channels.
  • Design and implement scalable data-processing workflows supporting knowledge-base synchronization, product-data updates, customer-data queries, and context preparation for AI responses.
  • Improve system stability, performance, error handling, and observability to ensure the AI customer-service platform reliably supports real customers.
  • Continuously research AI development tools, LLM application patterns, and agent workflows, and introduce suitable technologies into product development.
  • Work with the team to improve AI response quality, system maintainability, and product-development efficiency.

Desired Qualifications

  • Practical experience developing AI agents, retrieval-augmented generation (RAG), LLM workflows, prompt pipelines, tool calling, or evaluation flows.
  • Experience developing customer-service systems, CRM systems, chatbots, messaging platforms, e-commerce back offices, or SaaS back-office products.
  • Experience integrating LINE, Telegram, Slack, Zendesk, Salesforce, Shopify, WooCommerce, or other communication, customer-service, or e-commerce systems.
  • Experience processing large volumes of unstructured conversation, knowledge-base, product, or customer data.
  • Familiarity with background jobs, queues, schedulers, workers, or event-driven architecture.
  • Experience taking AI prototypes into production-ready systems.
  • Familiarity with observability, logging, monitoring, error tracking, and production debugging.
  • Enjoy using AI coding tools to improve development efficiency and be able to assess the quality and risks of AI-generated output.

About the Company

Raccoon AI

Enterprise AI solutions for customer service

Raccoon AI provides enterprise AI solutions that integrate with existing systems to boost efficiency for B2B clients in Asia. Its three core products are Raccoon AI Service, which automates multi-channel customer service workflows; Raccoon AI GEO, which turns first-party conversation data into AI-ready content to improve generative AI search visibility; and Raccoon AI Crew, which offers internal AI employees for Q&A, SOP lookups, data organization, and cross-functional collaboration. The company differentiates itself by combining external customer-service automation with internal knowledge management and data-driven collaboration, backed by James Chou’s experience and an extensive regional client base. Its goal is to help organizations increase lead conversion, streamline customer support, and improve internal operations by turning conversations and knowledge into actionable outcomes.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Taipei, Taiwan
Founded
2020

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