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Open nowPosted 2 days ago

QA Engineer

MyCareersFuture94,028 open roles

Pay
SGD 7,000 – SGD 9,000 a month
Where
Central, Singapore
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Your applicationOpen nowQA EngineerMyCareersFuture · Central, Singapore

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Share of postings closed within
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  2. 3.4%3 days
  3. 7.9%7 days
  4. 14.2%14 days
  5. 34.1%30 days
This job: posted 2 days ago

The posting

QA Engineer – AI Maintenance & Technology Upgrades

We are seeking a highly motivated QA Engineer to support the maintenance and continuous improvement of our Group Ops AI services. The role will focus on ensuring the quality, reliability, and stability of AI-powered applications during ongoing model upgrades, technology upgrades, platform enhancements, and production releases.

The successful candidate will work closely with AI Engineers, Data team, and our Technology partners to design, execute, and automate testing activities across the AI service lifecycle. This includes validating model performance, conducting regression testing, supporting release activities, and ensuring that upgrades do not negatively impact business processes or user experience.

Key Responsibilities:

Quality Assurance & Testing

  • Design, develop, and execute test plans, test cases, and test scripts for AI-powered applications and services.
  • Perform functional, integration, system, regression, and user acceptance testing (UAT) support.
  • Validate end-to-end workflows across AI applications, APIs, and integrated systems.
  • Identify, document, track, and verify resolution of defects and issues.

Model Upgrade Validation

  • Support testing and validation activities during AI model upgrades.
  • Conduct model output comparisons and regression testing to assess the impact of model changes.
  • Validate model performance against predefined quality metrics such as accuracy, relevance, consistency, and completeness.

Technology Upgrade & Release Support

  • Support testing for AI models during infrastructure, platform, security, and technology upgrades.
  • Validate system stability following upgrades to application frameworks, libraries, APIs, and supporting technologies.
  • Participate in release readiness reviews, production deployment validation, and post-release verification.
  • Ensure appropriate test evidence and documentation are maintained for audit and governance purposes.

Operational Support

  • Support production incident investigations related to model or technology changes.
  • Assist with root cause analysis and validation of fixes.
  • Monitor service quality trends and provide recommendations for quality improvements.
  • Work closely with Group Operations and Technology teams to ensure service reliability and business continuity.

Requirements:

Education & Experience

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.
  • 6-9 years of experience in software quality assurance, testing, or quality engineering.
  • Experience supporting enterprise applications, AI/ML solutions, or digital platforms is preferred.
  • Experience in banking, financial services, or operations environments is advantageous.

Technical Skills

  • Strong understanding of software testing methodologies and SDLC/STLC processes.
  • Experience with API testing tools such as Postman, Swagger, or equivalent.
  • Familiarity with SQL and data validation techniques.
  • Knowledge of test automation frameworks and scripting languages (e.g., Python, Selenium, Playwright).
  • Understanding of CI/CD pipelines and DevOps practices.
  • Familiarity with AI/ML or GenAI concepts, model testing, and prompt validation.
  • Exposure to monitoring, logging, and observability tools is a plus.

Functional Competencies

  • Strong analytical and problem-solving skills.
  • Ability to interpret test results and identify root causes of issues.
  • Excellent attention to detail and commitment to quality.
  • Strong communication and stakeholder management skills.
  • Ability to work independently in a fast-paced and evolving environment.

Preferred Skills

  • Experience testing AI, GenAI, chatbot, or machine learning solutions.
  • Experience validating model performance and conducting AI regression testing.
  • Knowledge of model governance, risk controls, and change management processes.
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