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Test Engineer with 3+ years in Manual, API, and AI-Assisted Testing across web, mobile, and desktop
Quality Analyst with 3.8+ years of experience in Manual and API Testing across Web, Mobile, and Desktop applications. Experienced in performing functional, regression, and end-to-end testing, ensuring application quality and stability throughout the software development lifecycle. Hands-on experience in API testing using Postman and Swagger, validating request/response structures and ensuring proper integration between services. Skilled in test case design, test execution, defect reporting, and test documentation while collaborating closely with development teams in Agile/Scrum environments. Currently working in the Loan Origination System (LOS) domain, validating loan processing workflows, monitoring Airflow DAGs, performing data validation using SSMS, and handling SFTP based file validations to ensure data accuracy and system reliability. Familiar with Microsoft Azure and experienced in client communication and cross-team collaboration.
St. Johns College of Engineering and Technology, Yemmiganur
B. Tech · Electronics and Communication Engineering
N/A – June 30, 2020
Flatworld Solutions
Software Test Engineer
August 1, 2025 – March 31, 2026
Bengaluru, Karnataka, India
Freetime Hospitality India
Software Tester
December 1, 2021 – December 31, 2024
Hyderābād, Telangana, India
Cultural Fit Analysis
The candidate's experience across different domains (LOS, Hospitality) and client bases (Netherlands, Germany, US mortgage clients) indicates adaptability and exposure to diverse work environments. The mention of client demos, documentation, and support, along with collaboration with internal teams, suggests a team-oriented and client-focused approach. The breadth of tools used also points to a willingness to learn and adapt to different tech stacks.
Soft Skills & Operational Fit
The candidate demonstrates good operational fit through experience in Agile/Scrum environments, client communication, and collaboration with internal teams. The ability to monitor Airflow DAGs and resolve issues within SLA timelines indicates a proactive and responsible approach. The use of AI-assisted tools for test case generation and documentation suggests an openness to leveraging modern technologies for efficiency.