hkex
AVP, Automation Testing Engineer, ITD
- Compensation
- Not disclosed
- Location
- CN-Shenzhen-HyQ
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 3+ years
- Category
- Not specified
- Posted
Skills
Must have
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related discipline.
- 8+ years of experience in software testing and quality engineering, including at least 3 years in a technical leadership role.
- Strong expertise in software testing methodologies, test planning, test automation, and quality engineering practices.
- Hands-on experience with automation testing frameworks and tools such as Selenium, Cucumber, Playwright, Cypress, or equivalent.
- Proficiency in programming and scripting languages such as Ruby, Python, Java, or JavaScript.
- Experience with CI/CD tools and practices, including Jenkins, GitLab, GitHub Actions, or equivalent.
- Solid understanding of Software Development Life Cycle (SDLC), Agile delivery methodologies, DevOps, and continuous testing practices.
- Practical experience using AI-powered tools to improve software testing or engineering productivity (e.g., GitHub Copilot, ChatGPT, Cursor, or equivalent).
- Understanding of AI-assisted testing concepts, including automated test generation, intelligent test maintenance, defect analysis, regression optimization, and test data generation.
- Strong analytical, troubleshooting, and problem-solving abilities.
- Excellent communication, stakeholder management, and collaboration skills.
- Demonstrated ability to lead technical initiatives and influence engineering teams.
Nice to have
- Experience in financial services, capital markets, trading platforms, exchange systems, clearing systems, or risk management applications.
- Experience implementing AI-enabled testing initiatives, proof-of-concepts, or productivity improvement programs within enterprise environments.
- Exposure to Large Language Models (LLMs), Generative AI applications, prompt engineering, or AI-assisted software engineering practices.
- Experience working in cloud-based environments and modern software delivery ecosystems.
- Ability to prioritize competing demands and deliver results under tight timelines.
- Experience leading geographically distributed teams or collaborating across multiple functions and locations.
Full description
Location:
CN-Shenzhen-HyQ
Shift:
Standard - 40 Hours (China)
Scheduled Weekly Hours:
40
Worker Type:
Permanent
Job Summary:
The AI-enabled Test Automation Lead is responsible for driving test automation strategy, framework development, and quality engineering practices across mission-critical applications, including trading, clearing, and risk management systems.
This role combines strong expertise in software testing and automation with the ability to leverage AI technologies to enhance testing efficiency, coverage, and quality. The successful candidate will lead the adoption of AI-assisted testing approaches, identify opportunities to streamline testing activities through Generative AI and intelligent automation, and provide technical leadership to testing teams.
Working closely with business, development, and quality engineering teams, the role will play a key part in improving software quality, accelerating delivery, and driving innovation in testing practices across the organization.
Job Duties:
Key Responsibilities
- Lead the design, development, and maintenance of test automation frameworks and solutions (e.g., Cucumber, Ruby, Selenium).
- Work closely with business, application development, and testing teams to design and implement scalable automation solutions for complex systems, including trading, clearing, and risk management platforms.
- Consolidate test libraries, automation assets, and tools across projects into reusable frameworks to improve efficiency and reduce duplication.
- Define and drive technical standards, governance, and best practices for test automation and quality engineering, ensuring alignment with enterprise standards.
- Lead continuous improvement initiatives to enhance software quality, improve testing effectiveness, and reduce time-to-market.
- Leverage AI technologies and tools to improve testing productivity, including test case generation, test data creation, automation script development, defect analysis, regression optimization, and test maintenance.
- Evaluate, pilot, and implement AI-assisted testing solutions to improve testing coverage, quality, and efficiency across projects.
- Collaborate with development and testing teams to identify opportunities for applying Generative AI and intelligent automation within the software testing lifecycle.
- Provide technical leadership, mentoring, and coaching to test engineers and automation specialists.
- Perform hands-on testing, automation development, scripting, troubleshooting, and technical problem-solving as required.
- Support project delivery by ensuring testing activities are executed effectively and quality risks are identified and managed appropriately.