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AI Application Developer

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Onsite

AI Application Developer

友邦科技

AI Application Developer

Skills

Mobile DevelopmentReactPythonJavaMicroservicesHTMLAILinuxProduct ManagerAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Chengdu, Sichuan, China

Work mode:

Onsite

Published on:

3 September 2026

What they need


该职位来源于猎聘 Roles and Responsibilities:

  • Focus on the release lifecycle for multiple AI-powered products: Copilot, RAG Platform, and Agentic AI deliverables.
  • Collaborate with development teams, architects, and design leads to ensure timely, high-quality releases.
  • Partner with Product Manager to elicit, document, and validate product requirements with business units across underwriting, claims, marketing, distribution, and IT.
  • Regularly engage with business unit stakeholders across the enterprise to gather requirements and feedback.
  • Translate business objectives and user feedback into actionable development items.
  • Participate in shaping the long-term platform portfolio strategy across generative AI offerings.
  • Leverage metrics (velocity, lead time, customer satisfaction) to iterate on process and product. Job Requirements:
  • Bachelor’s or above degree in Computer Science, Engineering, Information Systems, or related field.
  • 5+ years of experience in software engineering.
  • Front-end development experience included Angular, React, Vue or other similar frameworks well. JS, HTML5, XML, JSON, CSS, Ajax, Jquery;back-end development experience -Java, Python.
  • 5+ years’ experience in related language or platform: Cloud platforms, Linux/Windows/Unix platforms, Web/mobile applications
  • Knowledge of Software development life cycle (SDLC)
  • Proven experience delivering enterprise-grade software products in agile environments.
  • Adept at translating ambiguous business needs into tangible technical deliverables.
  • English can be used as working language. Preferred (not a must):
  • AI projects experience.
  • Understanding of GenAI architectures (LLMs, retrieval pipelines, vector stores) and enterprise integration patterns.
  • Familiarity with modern DevOps/CI-CD toolchains, cloud platforms (Azure preferred), and API-driven microservices.
  • Familiarity with MLOps, LLMOps, or similar AI delivery frameworks.

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