Binance Accelerator Program - Engineering

About Binance Accelerator Program

Who may apply

Responsibilities:

• Collaborate closely with product managers, traders, and researchers to build, test, and deliver high - quality AI - driven automated testing tools. Play a key role in integrating these tools into the product development lifecycle, blurring the lines between quality assurance (QA) and backend engineering (BE) efforts.
• Participate in product requirement document (PRD) discussions and code reviews. Provide technical insights from both testing and development perspectives, helping translate business needs into the design and implementation of AI - automated testing tools. Contribute to making these tools an integral part of the overall product development process.
• Design and execute comprehensive test plans for the AI - automated testing tools themselves. This includes functional testing to ensure accurate test case execution, end - to - end testing for seamless tool operation, and regression testing to maintain tool reliability as updates are made. Also, use the tools to conduct these types of testing on the products under development, enhancing the overall testing coverage and efficiency of the team.
• Identify, track, and help resolve bugs in both the AI - automated testing tools and the products being tested. Ensure that the timely and reliable delivery of both the tools and the end - products is maintained. Use debugging skills that span both testing and development domains to troubleshoot issues effectively.
• Develop and run automated test scripts using AI techniques for the testing tools. Continuously improve the efficiency and reliability of these scripts, which in turn boosts the QA process. These scripts should be flexible enough to be used across different projects and product types, serving as a core asset for the team's testing efforts.
• Conduct load and performance testing on the AI - automated testing tools. Ensure that the tools can scale to handle large - scale testing scenarios, which is crucial for the team to test products of varying complexity and size. Optimize the tools' performance to support the team's testing needs as the product portfolio grows.
• Focus on building and enhancing AI - automated testing tools that can be applied to backend optimization, QA automation, and identity verification use cases. These tools should be designed to work seamlessly with different technology stacks, including event processing models, web services, REST, Linux, MySQL, and cloud services, thus integrating well with the existing technical environment of the team.

Requirements:

• Currently pursuing or recently graduated with a degree in Computer Science, Software Engineering, or related fields.
• Have a solid understanding of software engineering principles, which should cover both development and testing aspects. Be familiar with QA methodologies, testing practices, and QA tools, as well as development - related concepts like coding, debugging, and system architecture.
• Have experience in at least one programming language (Java preferred, Python a plus). This language skill will be used for developing the AI - automated testing tools, writing test scripts, and making enhancements to the tools as needed.
• Be familiar with event processing models, web services, REST, Linux, MySQL, and cloud services. This knowledge helps in integrating the AI - automated testing tools with the existing technology ecosystem and ensures that the tools can be effectively used to test products built on these technologies.
• Have exposure to Agile/Scrum development and collaboration tools (e.g., Jira, Kanban). Understand how to work within an Agile framework to deliver the AI - automated testing tools in an iterative and collaborative manner, aligning with the team's development rhythm.
• Possess strong analytical and troubleshooting skills, with the ability to learn quickly. Be able to analyze problems that arise during the development and use of the AI - automated testing tools, whether they are related to tool functionality, integration issues, or product - under - test anomalies.
• Be self - motivated, detail - oriented, and collaborative. Thrive in a fast - paced environment where the AI - automated testing tools need to be developed and updated quickly to meet the team's testing demands. Work well with cross - functional teams including developers, product managers, etc., to achieve the common goal of improving the team's testing capabilities.
• Show curiosity about AI and its application in software engineering, especially in the context of building testing tools. Be willing to explore how AI can be further leveraged to enhance the functionality of the testing tools, such as improving test case generation, defect prediction, and test result analysis.
• Experience with financial products is a plus, but not required. If available, it can help in tailoring the AI - automated testing tools to better suit the needs of testing financial - related products, but the tools should be general enough to be applied across different domains.