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Staff Back-end Engineer (Business Support and Innovation) (AI)

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Страна
China
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Staff Back-end Engineer (Business Support and Innovation) (AI): LLM Multi-Agent , , with an accent on Agent Function Calling Focus on Agent/RAG Memory Long Context Planning Tool Use

Location: Shanghai, China

Date posted: 30.08.2026

Company

hirify.global is a global public commerce company building technology and services that simplify shopping, eating, and everyday life.

What you will do

  • Lead the architecture and core development of LLM- and multimodal-model-based multi-agent systems.
  • Build long-running hosted agents, sandbox execution environments, layered context management, persistent storage, and Function Calling orchestration.
  • Deliver complex Agent and RAG systems from solution design through production deployment.
  • Develop AI platforms for supply-chain automation, ordering assistance, inventory planning, and enterprise decision support.
  • Design and operate highly concurrent, highly available backend services.

Requirements

  • End-to-end production experience with complex Agent or RAG systems.
  • Knowledge of Memory, Long Context, Planning, and Tool Use, with the ability to turn research into production engineering.
  • Experience with one or more AI development frameworks, including LangChain, LangGraph, Deerflow, Claude Code, or Hermes.
  • Strong Java or Python skills and experience designing and launching large-scale distributed systems.
  • Understanding of asynchronous processing, concurrency, idempotency, rate limiting, design patterns, code quality, and maintainable architecture.

Culture & Benefits

  • Entrepreneurial startup culture combined with the resources of a large public company.
  • Opportunities to drive new initiatives and innovations in an always-on, high-tech commerce environment.
  • Hands-on work with cloud computing, data analytics, machine learning, and generative AI.

Hiring process

  • Application review, phone interview, onsite or virtual onsite interview, and offer.
  • Interview scheduling and results are communicated by email.

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