Help & Supportcareers@gravityer.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
QA Automation Engineer with 3+ years in Manual, Automation, API, and Performance Testing.
Results-driven QA Engineer with 3+ years of experience across Manual Testing, API Testing, Automation, and Performance Testing in P&C Insurance, Finance, and Property Management domains. Proven ability to design and execute comprehensive test strategies from user stories covering functional, regression, E2E, UAT, integration, smoke, sanity, and performance test cycles on web and mobile (iOS/Android). Hands-on with Selenium WebDriver (Java), POM, TestNG, REST/gRPC API testing (Postman), JMeter performance testing, SQL backend validation, and JIRA defect management. Experienced in Agile Scrum and Kanban environments. Passionate about quality engineering with a self-initiated AI/LLM integration POC demonstrating continuous learning.
UGMIT, Odisha
Diploma · Electrical Engineering
N/A – June 30, 2016
BPUT, Odisha
B.Tech · Electrical & Electronics Engineering
N/A – June 30, 2019
Ganatech Systems
Quality Analyst
June 1, 2022 – January 1, 2026
Hyderābād, Telangana, India
AI-Enabled QA Automation
June 28, 2026 – Present
Built a data-driven web automation framework using Selenium WebDriver + Java, POM, TestNG, and Apache POI applied business rule validations and identified latest valid records from large enterprise result tables. Integrated ChatGPT API (LLM) into the automation pipeline to auto-generate AI-powered, human-readable summaries from raw test/monitoring data exploring AI's practical role in QA reporting. Configured Jenkins (basic) for scheduled pipeline execution with email notifications, duplicate checks, logging, and exception handling; managed source code via Git & GitHub.
Cultural Fit Analysis
The candidate's experience across various testing types (manual, automation, API, performance) and domains (insurance, property management) indicates adaptability. The personal project involving AI/LLM integration shows a willingness to explore new technologies and innovate, which aligns well with a forward-thinking culture. Their participation in Agile sprints suggests a collaborative mindset. The breadth of tools and methodologies used points to a versatile individual who can integrate into diverse technical environments.
Soft Skills & Operational Fit
The candidate demonstrates a proactive attitude through their personal AI-enabled QA automation project. Their experience in Agile environments suggests good team collaboration and adaptability. The detailed descriptions of their work indicate a structured approach to problem-solving and defect management. However, without direct assessment data, specific soft skill strengths like communication under pressure or conflict resolution cannot be fully evaluated.