Specialist, Software Quality and Automation

Location: Singapore

The Digital department at INSEAD supports the school's global operations by delivering cutting-edge technological solutions that enhance teaching, research, and administrative functions. It ensures seamless integration of digital tools and infrastructure across all campuses, fostering innovation and operational efficiency.

INSEAD Digital is seeking for a Software Quality and Automation Engineer that can support and lead multiple products by means of automation of regression testing, Business manual processes and ensures that Software Quality Assurance best practices are implemented to deliver a quality product. The Software Quality and Automation Engineer will follow the full Agile Scrum lifecycle from development until deployment.  This is a full-time, permanent contract position based at either our Asia Campus in Singapore. A hybrid working model is in place – 3 days on campus, 2 days from home.

The Specialist, Software Quality and Automation is also expected to leverage Artificial Intelligence (AI) and intelligent tooling to enhance software quality practices, including defect analysis, test optimization, and quality risk assessment. The role will contribute to the adoption of AI‑assisted quality engineering to improve efficiency, insight, and decision‑making across Digital products. 

Your role within the team

Test Automation Framework: 

• Implementation and maintenance of the Software Quality Assurance Framework from test automation solution, designing automation frameworks, CICD, test strategy, test plans and test execution of the product. 
• Supports automation script development and the optimization of those scripts. 
• Create and execute automated tests, track defects and report results. 
• Recommends new tools, techniques and methodologies needed to enhance productivity and quality. 
• Collaborate with Digital teams/vendor to strategize and align long term solution for test automation including roadmap, tools, framework, and approach. 
• Develop automation strategy to support regression testing based on technical analysis, complexity, and reusability 

AI‑Enabled Quality Engineering: 

• Apply AI‑assisted tools and techniques to improve test coverage, defect detection, and quality insights. 
• Leverage AI capabilities to:  
• Analyze defect trends and recurring quality issues 
• Identify quality risks in releases and regression scopes 
• Support intelligent test selection and prioritization 
• Collaborate with Digital and Quality Management teams to support AI initiatives in QA, including knowledge discovery, reporting automation, and quality analytics. 
• Contribute to the design, implementation, or usage of AI agents or copilots (e.g. for quality insights, defect analysis, or reporting). 
• Continuously evaluate emerging AI and ML capabilities relevant to software testing and quality engineering. 

The ideal candidate profile 

• At least 1 to 2 years’ experience in test automation or related field. 
• Proficiency in Tosca for test automation. 
• API Testing using Postman 
• Strong experience in Automation Web Applications using Selenium Web driver, Grid with TestNG, Maven and BDD (cucumber). 
• Experience in preparing feature files and automated the feature file using Selenium. 
• Used GitHub, source code management tool for code repository for Automation Testing 
• Has significant experience in IT and especially software testing theories, principles and practices. 
• Has significant experience in functional and technical tests (both manual and automated). 
• Worked in an Agile environment (SCRUM). 
• Implemented CI/CD Automation using JENKINS 
• Worked with various development languages (C#, Javascript, Java, PHP).  
• Worked with various environments (Windows, Linux, AWS). 
• Worked with test automation tools (at least Selenium, Python, Tosca, PHPUnit). 
• Worked with continuous integration tools (at least Jenkins & GitHUB). 
• Worked with Digital project/product management tools like Jira. 
• Experience or demonstrated exposure to AI‑assisted testing, quality analytics, or intelligent automation.  
• Hands‑on experience using AI features within testing, DevOps, or delivery platforms (e.g. Jira / Atlassian ecosystem, test analytics tools, defect analysis tools).  
• Experience analyzing large sets of test or defect data using AI‑driven or data‑assisted approaches.  
• Understanding of how AI can be applied to:  
  • Test optimization 
  • Defect prevention 
  • Quality risk management 

Kindly submit your application along with a CV in English.