Taiwan, Taipei && South East Asia && Vietnam, Ho Chi Minh && Thailand, Bangkok && Hong Kong && Australia, Brisbane && Australia, Melbourne && Australia, Sydney && Asia
Full-Time
Mid (3-6 yrs)
Engineering & Development
Posted on February 7, 2023
About the team
Binance Square is a social content and discovery platform within the Binance ecosystem, serving millions of users with real-time market insights, creator-driven content, and AI-powered recommendations. The AI & Data Services team builds the backend infrastructure that powers content discovery, personalized feeds, and intelligent data services across the platform.
Responsibilities:
Design, develop, and maintain high-performance backend services for the Binance Square product, focusing on content discovery, recommendation pipelines, and AI-powered features
Build and operate scalable microservices handling millions of daily requests, ensuring reliability, low latency, and graceful degradation under peak load
Integrate Large Language Models (LLMs) and AI/ML pipelines into production backend systems, including RAG architectures, prompt orchestration, and agentic workflows
Collaborate closely with Product Managers, Data Scientists, DevOps, and frontend engineers to deliver end-to-end solutions from data ingestion to user-facing features
Design and optimize data pipelines for content indexing, real-time analytics, and ML feature serving
Advocate for engineering best practices — conduct code reviews, write comprehensive tests, and drive architectural improvements
Troubleshoot and resolve production issues, performing root-cause analysis and implementing preventive measures
Contribute to technical design documents and participate in architecture decision-making
Requirements:
3–6 years of back-end software development experience with strong proficiency in Java (primary) or Golang/Python
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Deep understanding of software frameworks, design patterns, and microservices architecture
Strong experience with relational databases (MySQL/PostgreSQL), message brokers (Kafka/RabbitMQ), and caching systems (Redis)
Experience with cloud infrastructure (AWS/GCP/Azure) and containerization (Docker/Kubernetes)
Hands-on experience integrating AI/LLM technologies into production systems — RAG, prompt engineering, LLM orchestration, or agentic pipelines is a strong plus
Experience with high-throughput, low-latency backend systems serving millions of users
Solid understanding of data structures, algorithms, and system design
Ability to work independently and communicate effectively in a distributed, cross-timezone team environment
