Expert Software Engineer - ShopeePay

Shopee; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ShopeePay, the payment arm of Shopee, seeks a backend-focused engineer to design and build scalable payment systems with high concurrency and reliability. You will work on financial services and AI-enabled engineering practices, while ensuring data integrity, security, and disaster recovery.

Collaboration across Shenzhen, Singapore, and Indonesia is integral to the role. The role emphasizes distributed systems, cloud infrastructure, and end-to-end product delivery, with a mix of backend work and

Qualifications

• 5+ years of backend development experience in scalable services (payments/financial systems preferred).
• Strong experience with Golang, Java, or Python; Golang preferred.
• Familiarity with MySQL, Redis, Kafka, Linux, and cloud infrastructure.
• Experience using AI to improve testing, debugging, incident response, or production operations is a strong plus.

Responsibilities

• Design and develop high-concurrency, highly available payment systems.
• Build critical payment modules with strict security, integrity, and disaster-recovery requirements.
• Participate in end-to-end product delivery from design to deployment and operations.
• Apply AI coding tools throughout the development lifecycle and build AI-native engineering practices.
• Collaborate across regions to deliver reliable backend services for ShopeePay.

Skills

Golang

Java

Python

Distributed systems

High-volume transactions

MySQL

Redis

Kafka

Linux

Cloud infrastructure

CS fundamentals

Algorithms & data structures

AI tooling

AI workflows

Ownership

Tools

Git

CI/CD pipelines

Job description

ShopeePay is Sea’s payment business and a key foundation for Monee’s financial products. Our cross-regional R&D team is based in Shenzhen, Singapore, and Indonesia.

We provide secure and reliable payment and payout services for millions of merchants and users across Southeast Asia, Latin America, and other markets. Our systems support e-commerce, food delivery, digital payments, and a wide range of financial scenarios.

This is a backend-oriented full-stack role. Backend architecture, distributed systems, payment reliability, and AI-assisted engineering are the primary focus. Basic frontend capability is sufficient to help deliver complete product features.

Job Description:

• Design and develop high-concurrency, highly available, and high-performance payment and financial systems.
• Build critical payment modules with strict requirements for fund security, data integrity, consistency, and disaster recovery.
• Participate in end-to-end product delivery, from business understanding and system design to implementation, testing, deployment, and operations.
• Use AI coding tools throughout the development lifecycle, including design, coding, testing, debugging, refactoring, and code review.
• Build AI-native engineering practices, including Agent Harnesses, engineering Knowledge Bases, AI Loops, workflow automation, and knowledge reuse.

Requirements:

• Strong backend development experience with Golang, Java, or Python. Golang is preferred.
• At least 5 years of experience building scalable backend services, distributed systems, or high-volume transaction systems. Experience in payment, e-wallet, banking, or other financial systems will be a strong plus.
• Prior experience using AI to improve testing, debugging, incident response, code quality, or production operations in a implementation setting will be a strong plus.
• Familiarity with MySQL, Redis, Kafka, Linux, and common cloud or infrastructure technologies.
• Good understanding of computer science fundamentals, including data structures and algorithms, operating systems, computer networks, databases, and distributed systems.
• Strong logical thinking and problem-solving skills. You can understand complex systems, identify key constraints, and make sound technical decisions.
• Practical experience using AI coding tools to improve development speed and quality.
• Experience or strong interest in building AI engineering workflows, including:
• Agent Harnesses for context management, tool use, execution, feedback, and quality control.
• Engineering Knowledge Bases containing architecture, business, API, coding, and operational knowledge.
• AI Loops covering task decomposition, context preparation, AI generation, execution, testing, review, iteration, and knowledge accumulation.
• Strong ownership experience, communication skills, and collaboration experience.