KERING Applied AI Engineer-Agentic Applications

Summary

You will own the technical delivery of assigned applications, from requirements and prototypes through testing and production support. Working with the Principal AI Engineer and platform team, you will build on shared AI services, review partner-developed components and bring selected applications into in-house development.

Job Description

Product Discovery & Requirements

• Work with product managers, business analysts and users to understand tasks and pain points. Contribute to product requirements, user stories and acceptance criteria, including how the agent should handle exceptions.
• Prototype workflows, test assumptions with users and recommend changes to scope or behavior when a simpler approach would better meet the need.

AI Application Development & Evaluation

• Build agents and workflows in Dify, with Python extensions where needed. Use shared model access and business APIs to implement prompts, tool calls, structured outputs and state management.
• Develop retrieval and context assembly using shared knowledge services. Improve document preparation and retrieval quality while preserving source references and users’ data access permissions.
• Integrate agent tools with Java/Spring business services through documented APIs. Implement validation, approval steps and error handling; agree response and streaming contracts with frontend engineers.
• Maintain scenario-based evaluations and regression tests. Use production traces and user feedback to improve prompts, retrieval, tools and agent behavior, measuring quality, response time and cost.

Delivery Ownership & Collaboration

• Version code, Dify workflows, prompts, tests and deployment configurations. Work with QA and operations colleagues on releases, production issues and improvements through shared engineering controls.
• Review partners’ code, prompts, workflow definitions and test evidence. Resolve issues and complete handovers that allow the team to reproduce, support and evolve selected applications.
• Use AI-assisted development tools in daily engineering work, review their outputs and contribute reusable code and lessons to the team.

Who you are?

Experience & Technical Skills

• Bachelor’s degree or above in Computer Science, Software Engineering, or a related field.
• At least four years of software or AI engineering experience, including hands-on delivery and maintenance of LLM applications or AI agents in production.
• Strong Python skills, including API integration, structured data handling and automated testing.
• Practical experience with Dify or comparable agent and workflow platforms, including tool use, structured outputs and multi-step execution.
• Experience with retrieval-augmented generation (RAG), embeddings, vector search and prompt design, and an understanding of how retrieval and context affect application quality.
• Experience evaluating AI application behavior, reading execution traces and turning failures into tests and improvements.
• Working knowledge of REST/OpenAPI integration, authentication, access control and databases, together with Git, CI/CD and containerized application delivery.
• Ability to trace requests across applications, agents and tools, and handle timeouts, retries and user or tenant context correctly.
• Ability to clarify ambiguous requirements with product and business colleagues and turn them into testable application behavior.
• luency in Mandarin and good working proficiency in English.

Preferred Experience

• Experience maintaining or taking over externally developed applications.
• Experience integrating Python or Dify applications with Java/Spring services, or implementing tools through Model Context Protocol (MCP).

Personal Attributes

• You ask what users are trying to achieve and contribute ideas about how the application should work.
• You take responsibility for the software you deliver, including its behavior after launch.
• You work openly with colleagues, communicate problems early and use feedback to improve your work.

Job Type

Start Date

Schedule

Organization