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Backend Engineer

Design, build and run the production backend behind our core business, data services and AI applications, from solution design through load testing, release and incident review.

Monthly pay
¥11–20K / month
Experience
Any experience level
Education
Any degreeNo degree or major requirements
Location
Tianhe, Guangzhou

Why join

  • Design, build, optimize and review real production systems, not side projects or outsourced work
  • Build the backend for AI products, including LLM inference services, agent workflows and data pipelines
  • AI-assisted development across the team, with unlimited Claude and Codex usage
  • A flat, young team with mentorship, focused on problem solving and shipping

What you will do

  • Design, code and operate backend services across the full lifecycle: requirements review, solution design, development, load testing, release and incident review
  • Build core business systems, including APIs, async jobs, message consumers, data services and internal admin platforms
  • Contribute to middleware, shared components and platform capabilities that cut duplicate work and speed up development
  • Help build monitoring, logging, alerting, rate limiting, degradation and disaster recovery to keep services stable and within SLA
  • Work with product, frontend, AI, data and infrastructure teams to turn business needs into stable, scalable, maintainable services

What we look for

  • Strong command of at least one of Go, Python, Java, Rust or C++, with solid algorithms and data structures, and comfort with Linux development and network troubleshooting
  • Proficiency with common backend components such as MySQL/PostgreSQL, Redis and Kafka/RabbitMQ
  • Understanding of RPC, microservices and distributed systems fundamentals, including service decomposition, cache consistency, idempotency, retries and rate limiting
  • Cloud-native basics with Docker and Kubernetes, including deployment, scaling, log monitoring and distributed tracing
  • Experience diagnosing production incidents, tuning performance or improving stability, using logs, metrics and traces
  • You use AI tools to work faster while still judging code quality and system risk for yourself

Nice to have

  • Experience building LLM inference services, RAG or agent workflows
  • Experience with real-time computing or big data tools such as Flink, Spark, ClickHouse or Doris
  • Experience with Kubernetes, CI/CD, observability, reliability engineering or service governance

Growth path

An architect who can own systems end to end

Tech stack

  • Go
  • Gin
  • Python
  • MySQL
  • PostgreSQL
  • Redis
  • Kafka
  • RabbitMQ
  • Docker
  • Kubernetes

Apply for this role

Email your CV with the role name in the subject line, or message us directly on BOSS Zhipin.