Job Responsibilities
AI Business Implementation: Design and develop AI-driven application tools tailored to real business scenarios such as e-commerce, LeXiang , and internal operations—including intelligent Q&A, automated processing assistants, and data analysis agents—to improve operational efficiency.
Intelligent System Development: Build RAG (Retrieval-Augmented Generation) systems based on existing business data and knowledge bases, enabling AI to accurately access internal enterprise information and support customer service, operations, and decision-making scenarios.
AI Agent Development: Develop intelligent agents with task execution capabilities, integrating with existing business systems to achieve workflow automation and intelligent assistance, reducing repetitive manual work.
Productization & Delivery: Work closely with business teams to package AI capabilities into user-friendly internal tools or product features, driving adoption from pilot projects to scaled deployment.
Continuous Optimization: Stay current with AI technology advancements, optimize model performance, response speed, and user experience based on business feedback, ensuring AI applications remain stable and reliable.
Job Requirements
Technical Foundation: Proficient in Python or Java , etc , familiar with frontend and backend development, with hands-on experience in engineering and productizing AI capabilities.
AI Application Experience: Familiar with LLM API integration, RAG architecture, and AI agent development, with proven success stories of implementing AI technology in real business contexts.
Business Acumen: Background in e-commerce or enterprise operations, with the ability to quickly understand business pain points and propose feasible AI-driven solutions.
Collaboration Skills: Strong communicator who can translate technical concepts into business value, effectively collaborating with product, operations, and business teams to drive cross-functional initiatives.
Learning Mindset: Passionate and curious about AI technology, eager to experiment with new approaches and solve emerging challenges in a fast-paced environment.
Nice to Have
Experience with internal AI tools, intelligent customer service, or AI assistant projects
Familiarity with mainstream domestic large language models and enterprise deployment solutions
Data analysis and visualization skills, with the ability to leverage AI for business decision support
