Quality Assurance Engineer - Onsite

Job Summary

Test Lead role in a global organization responsible for validating complex generative artificial intelligence solutions and application programming interfaces using tools such as Swagger and Postman. The role ensures reliable open interface definitions and secure gateway integration in a hybrid work model with focus on quality compliance and customer value.

Responsibilities

• Drive end to end test planning for generative artificial intelligence solutions ensuring alignment with architecture business expectations and compliance standards
• Design comprehensive test strategies for application programming interfaces including functional performance and security aspects to ensure reliable service interactions
• Coordinate creation and maintenance of reusable test scenarios and data sets for open application interfaces using structured and consistent approaches
• Manage defect life cycle across multiple releases by documenting issues with clear evidence impact analysis and risk based prioritization for timely closure
• Execute manual and automated tests for gateways and microservice interfaces using tools such as Swagger and Postman to validate contract compliance and resilience
• Review interface specifications and open interface definitions to identify ambiguities gaps and risks and provide clear feedback to development and product teams
• Collaborate with product managers and engineers to refine acceptance criteria and trace requirements to test cases ensuring full coverage and audit ready documentation
• Guide test team members by clarifying test approaches reviewing test artefacts and promoting consistent quality practices across distributed hybrid teams
• Implement metrics and dashboards that track defect trends coverage stability and test progress to provide transparent status and support data informed decisions
• Optimize regression packs and test environments to shorten validation cycles while maintaining depth of coverage for critical generative artificial intelligence and interface flows
• Coordinate user acceptance support activities by preparing test data clarifying scenarios and analyzing outcomes to ensure smooth sign off for production releases
• Apply risk based testing techniques focusing on scenarios that impact data integrity privacy and reliability especially when handling sensitive health related data sets
• Align testing activities with organizational quality frameworks ensuring adherence to industry regulations and internal standards relevant to health data processing

Qualifications

• Possess extensive experience in testing generative artificial intelligence enabled applications including validation of prompts responses model integration and safety checks
• Demonstrate strong proficiency in testing application programming interfaces using Swagger Postman and related tools with focus on request response validation and error handling
• Exhibit solid understanding of gateway configurations including routing throttling and authentication policies and how these affect end to end integration testing
• Apply practical knowledge of open interface specifications to design tests that validate consistency version control and backward compatibility across services
• Bring experience in hybrid work environments with proven ability to collaborate effectively across onsite and remote teams using structured communication and documentation
• Leverage familiarity with health data collection processes and concepts to design test scenarios that respect privacy consent and data quality considerations even if domain exposure is limited
• Show capability in using scripting or automation frameworks to create repeatable interface tests that support continuous integration pipelines and frequent releases
• Display strong analytical and problem solving skills with focus on root cause identification clear communication and continuous improvement of test practices

Certifications Required

ISTQB Advanced Test Manager or equivalent plus certification or coursework in API testing or generative artificial intelligence testing