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QA Engineer with 3+ years in AI-driven platforms & mobile/web testing.
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Results-driven QA Software Engineer with 3+ years of experience delivering high-quality software solutions across Healthcare, Logistics, and AI-driven platforms, specializing in mobile, web, and API testing. Skilled in designing and executing test strategies, performing defect analysis and root cause identification, and ensuring reliable release validation within Agile environments. Familiar with test automation and CI/CD-aligned QA practices, with strong debugging skills using logs and API validation tools. Proficient in leveraging AI tools for test case generation, data creation, and process optimization to enhance testing efficiency and product quality
Hindusthan college of engineering and technology
Bachelors · Mechanical Engineering
August 1, 2020 – June 30, 2020
Test Yantra Software Solutions India Pvt Ltd
Software Engineer(Quality)
July 1, 2022 – Present
Bengaluru, Karnataka, India
AI-Powered Health & Nutrition Tracking Application (USA)
July 1, 2022 – June 1, 2026
Owned end-to-end QA for an AI-driven mobile app, aligning QA strategy with product goals. Validated AI/LLM outputs (calories, macros, conversational flows, fallback logic). Performed RCA on critical defects (data inconsistencies, sync issues), improving reliability. Tested complex workflows: multi-ingredient meals, AI edits, real-time updates (WebSockets). Leveraged AI tools for test case generation, data creation, and exploratory testing. Identified defect trends and risks, contributing to process improvements and better coverage. Executed regression, integration, and production testing across chat and nutrition modules. Collaborated with cross-functional teams to refine acceptance criteria and ensure quality delivery.
Injury Recovery & Social Health Application (USA)
July 1, 2022 – June 1, 2026
Designed and executed 100+ API test cases using Postman, reducing API defects. Logged and tracked 200+ defects in JIRA, improving QA-Dev collaboration. Conducted cross-platform testing (Android & iOS), minimizing release risks. Performed functional, integration, and regression testing for stable releases. Analyzed defect patterns and contributed to RCA and preventive QA strategies. Actively participated in Agile ceremonies, improving sprint quality and timelines. Used AI tools for test data generation and faster issue identification. Supported debugging using API responses and logs for quicker issue resolution.
Logistics & Shipment Tracking Application (USA)
July 1, 2022 – June 1, 2026
Performed end-to-end testing of real-time shipment tracking and delivery workflows. Designed and executed 100+ test cases with high accuracy and documentation standards. Conducted defect trend analysis and RCA, improving product quality by 25%. Validated business-critical flows: tracking, notifications, delivery timelines. Identified risks in real-time data handling and ensured system stability. Collaborated with stakeholders to align QA deliverables with business needs. Contributed to QA planning, estimation, and task prioritization. Supported performance testing efforts and concurrency validations.
Cultural Fit Analysis
The candidate's experience across diverse domains (Healthcare, Logistics, AI-driven platforms) suggests adaptability and a broad understanding of different business contexts. Their active participation in Agile ceremonies and collaboration with cross-functional teams indicates a team-oriented mindset. The use of AI tools for test case generation and data creation shows a willingness to embrace innovation and new technologies, which is a positive cultural fit for forward-thinking organizations. The focus on improving product quality and reducing defects aligns with a culture of excellence.
Soft Skills & Operational Fit
The candidate demonstrates strong collaboration skills through participation in Agile ceremonies and working with cross-functional teams. Their experience in defect trend analysis and RCA suggests a proactive and analytical approach to quality improvement. The use of AI tools for test data generation and issue identification indicates an adaptability to new technologies and a focus on efficiency. The candidate's professional summary highlights being 'results-driven' and 'proficient in leveraging AI tools,' which aligns with modern operational needs for efficiency and quality.