AI-Assisted Software Engineer – Fintech

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally. Job Responsibilities/ 工作职责 : We are looking for an AI-Assisted Software Engineer to join our fintech technology team in Nanshan, Shenzhen. This is not a traditional software engineering role. We are looking for engineers who embrace an AI-first development mindset and can effectively use AI coding tools such as Claude Code, GitHub Copilot, ChatGPT, Cursor, or similar AI development agents to accelerate the entire software development lifecycle. You will participate in the complete lifecycle of fintech products — from requirement analysis, solution design and architecture, to coding, testing, deployment, monitoring and production support. The ideal candidate combines strong software engineering fundamentals with the ability to work effectively with AI tools while maintaining high standards for code quality, security, reliability and compliance . Key Responsibilities

1. AI-Assisted Software Development · Use AI coding agents and development tools to improve software development productivity and quality. · Apply AI throughout the development lifecycle, including: o Requirement analysis o Technical planning o Solution and architecture design o Code generation o Code refactoring o Code review o Unit and integration testing o Debugging o Documentation o Deployment preparation o Production troubleshooting · Convert business requirements into clear technical implementation plans. · Review, validate and improve AI-generated code before production use. · Understand when to use AI automation and when human engineering judgement is required. · Continuously explore new AI engineering tools, workflows and development practices.
2. Fintech Product Development · Design, develop and maintain secure and scalable fintech applications and services. · Participate in development of systems such as: o Payment gateway o Payment APIs o Merchant integration o Card payments o QR payments o E-wallet payments o Bank transfers o Refunds o Settlement and reconciliation o Payout and disbursement o Merchant management · Integrate with banks, payment channels, card networks and third-party service providers. · Develop secure APIs, backend services and transaction-processing components. · Ensure payment transactions are reliable, traceable and protected against duplicate processing.
3. Software Engineering · Write clean, maintainable, secure and production-ready code. · Participate in system design and architecture discussions. · Develop REST APIs, microservices, event-driven services and backend applications. · Apply appropriate software engineering principles and design patterns. · Implement proper: o Error handling o Retry mechanisms o Idempotency o Timeout management o Rate limiting o Logging o Monitoring · Perform code reviews and contribute to engineering standards. · Identify and reduce technical debt.
4. Testing and Quality Engineering · Use AI to assist in generating and improving test cases. · Develop unit, integration and automated tests. · Participate in functional, regression, performance and security testing. · Ensure critical payment flows have sufficient automated test coverage. · Investigate defects and identify root causes rather than applying temporary fixes. · Improve software quality through continuous testing and automation.
5. DevOps and Deployment · Participate in CI/CD and automated software delivery. · Deploy and maintain applications in cloud and container environments. · Work with Docker, Kubernetes and modern deployment platforms where applicable. · Support: o Automated deployment o Canary deployment o Blue-green deployment o Rollback o Environment configuration · Work closely with DevOps/SRE teams to improve deployment reliability. · Participate in production monitoring and incident troubleshooting. AI-First Engineering Expectations Candidates should be comfortable treating AI as an engineering partner rather than simply a search or autocomplete tool. You should be able to: · Break complex engineering problems into tasks suitable for AI agents. · Provide clear technical context and instructions to AI coding tools. · Use AI agents to inspect and understand unfamiliar codebases.

· Generate implementation plans before coding. · Ask AI to propose multiple technical approaches and evaluate their trade-offs. · Use AI to generate tests before or alongside implementation. · Use AI for debugging, log analysis and root-cause investigation. · Review AI-generated code for correctness, security and maintainability. · Detect AI hallucinations and technically incorrect recommendations. · Prevent sensitive company and payment information from being exposed to unauthorized AI services. The objective is not simply to generate more code, but to deliver better software faster with fewer defects and less repetitive engineering work . Security and Fintech Requirements · Follow secure software development practices. · Understand common application and API security risks. · Protect sensitive information, credentials, API keys and payment data. · Apply appropriate authentication and authorization controls. · Understand encryption, tokenization and secure data handling concepts. · Follow company security and change-management policies. · Familiarity with PCI DSS and payment industry security requirements is highly desirable. · Experience developing systems within regulated or security-sensitive environments is an advantage. Technical Requirements Candidates should have practical experience with several of the following: · Java / PHP / Go / Python / Node.js / C# or similar backend languages · RESTful APIs · Microservices · SQL and relational databases · MySQL / PostgreSQL / MariaDB or similar databases · Redis or equivalent caching technologies · Kafka / RabbitMQ or other messaging technologies · Git and modern source-control workflows · Linux environments · Docker · Kubernetes · CI/CD pipelines · Cloud platforms such as AWS, Alibaba Cloud, Tencent Cloud, Huawei Cloud or Azure Strong fundamentals are more important than experience with any single programming language. Qualifications · Bachelor’s degree in Computer Science, Software Engineering, Information Technology or related discipline. · Approximately 3+ years of professional software development experience; exceptional candidates with less experience may also be considered. · Strong programming and problem-solving fundamentals. · Practical experience using AI coding assistants or AI development agents. · Ability to independently analyze requirements and deliver software solutions. · Good understanding of databases, APIs and backend system development. · Experience with fintech, payments, banking or financial systems is strongly preferred. Preferred Qualifications Candidates with the following experience will have an advantage: · Payment gateway or payment-processing systems · High-volume transaction platforms · Financial reconciliation or settlement systems · PCI DSS environments · High-availability architectures · Cloud-native applications · Microservices and distributed systems · DevSecOps · Automated testing · AI agent workflows · AI-assisted code review or testing · Production incident troubleshooting Collaboration & Language · Able to work independently with minimal supervision. · Comfortable collaborating with engineering teams outside China. · Able to read and understand English technical documentation. · Able to communicate technical topics in English through email, chat and technical meetings. · Strong communication, ownership and teamwork mindset. What Success Looks Like A successful AI-Assisted Software Engineer should be able to: · Deliver reliable fintech features faster with the help of AI. · Reduce repetitive coding and manual development activities. · Increase automated testing and software quality. · Solve production issues efficiently. · Produce secure and maintainable code. · Use AI without compromising security or engineering standards. · Continuously improve development workflows. · Contribute to a culture where engineers focus more on architecture, problem-solving and product quality , while AI handles more repetitive implementation work. Ideal Candidate You are a software engineer who believes the future of software development is Engineer + AI , not Engineer versus AI. You are comfortable asking AI to help plan, code, test, review, debug and document software — but you also have the engineering knowledge to challenge its answers. You care about building secure, reliable and scalable financial systems, and you are excited about using AI to fundamentally improve how software is engineered and maintained. Pre-Requisites/ 任职要求 : Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best. Are you game?