[Growth Engineering] Staff Back-end Engineer I
On-site · Shanghai, Shanghai, China
Job Summary
Growth Engineering Staff Back-end Engineer I responsible for building AI-native data platforms and scalable backend systems. You will design and implement low-latency data infrastructure with LLM-powered analytics, retrieval-augmented generation loops, and AI copilots integrated into the software development lifecycle. Key work areas include Enterprise Knowledge Graph & agentic RAG systems, automated evaluation and governance for AI systems, and cross-regional collaboration across Shanghai, Seoul, and the US. Preferred qualifications include experience with Python/FastAPI, vector and graph databases, MLOps tooling (Triton MLflow), LangGraph, and strong English communication; opportunity to own end-to-end lifecycle from research to production on one of the world's largest e-commerce platforms. This role emphasizes building from scratch with modern tooling, ownership of end-to-end delivery, and impact on millions of users.
Desired Qualifications
- Orchestration & Data Infrastructure: High-performance frameworks (Python/FastAPI)
- Stateful graph orchestration frameworks (e.g., LangGraph)
- Vector DBs and Graph DBs
- MLOps & Observability tools for containerized model deployment and evaluation monitoring (e.g., Triton Inference Server, MLflow)
- Global collaboration and effective English verbal and written communication across regional hubs (Shanghai, Seoul, US)
- Experience building AI-native data platforms and analytics
- Experience with retrieval-augmented generation (RAG) loops and knowledge graphs
- Experience designing AI copilots and AI-assisted software development lifecycles
- Back-end infrastructure and scalable production systems
- Cross-regional collaboration and enterprise-scale delivery
- AI governance, data privacy, and cost efficiency in engineering practices
- Experience with Text-to-SQL/Text-to-API analytics
- Knowledge of LLM evaluation and governance frameworks
- Hands-on experience with modern tooling for AI engineering and production workflows
- Experience with enterprise-grade data platforms and low-latency systems
- Experience with CI/CD pipelines in production environments
- Strong software engineering fundamentals (Python preferred)
- Experience with distributed systems and scalable backend architectures
- Familiarity with LangGraph, vector embeddings, and semantic search
- Knowledge of data platforms that support AI-native analytics
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