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QA Automation Engineer with 4+ years in Web and API Testing
With 5 years in the IT industry and 4 years specializing in QA testing, I possess strong expertise in manual and automation testing of web and API applications. Skilled in analyzing business and system requirements, I design and execute comprehensive test strategies, plans, and cases. Proficient in functional, regression, UI, integration, cross browser, black box, and system testing across SaaS core and logistics domains. Experienced with Agile methodologies, JIRA bug tracking, and SDLC processes. Competent in end to end automation testing using Playwright (JavaScript/TypeScript), Selenium (Java), and API testing with Postman. Familiar with MCP Servers and Agentic AI for VS Code integration. Testing AI/agent-based product features, including LLM logic and agent workflows. Evaluating prompt quality, model responses and overall output reliability. ISTQB Foundation level Certified Tester from Indian Testing Board
Calicut University
B.Tech/B.E.
N/A – June 30, 2010
Andersen Lab
Automation QA Engineer
June 1, 2026 – Present
India
Vanilla Network PVT LTD
QA Software Tester
January 1, 2025 – May 1, 2026
India
Rippey.ai
QA Engineer
October 1, 2022 – November 1, 2024
India
RPA Labs(Now Rippey.ai)
Process Analyst
June 1, 2022 – September 1, 2024
India
Valuebound Solutions Pvt Ltd
Content Writer Technical
May 1, 2014 – April 1, 2015
India
AI Manual Test Case Generator with Java
May 1, 2026 – June 1, 2026
Utilized Java 21 and Maven to develop a robust application integrating Ollama (Llama3) for local large language model (LLM) processing via REST API. Designed and implemented functionality to read requirement files and generate structured prompts, enhancing test case accuracy by more than 85%. Enabled intelligent test case generation through offline, cloud independent execution, improving data security and reducing runtime by 40%. Explored advanced integration of AI and QA through prompt engineering and local LLM API handling in Java. Advanced automation capabilities beyond traditional Selenium frameworks, increasing testing efficiency and reducing manual documentation efforts by 40%. Transitioned from manual documentation to AI assisted productivity, accelerating quality assurance workflows and reducing time to market.
AI Powered API Test Automation Generator
April 1, 2026 – May 15, 2026
Developed an AI driven API test automation platform using n8n, AI agents. Playwright, and Node.js. Built workflows that accept API specifications, generate Playwright test scripts using AI, and automatically execute them through Node.js watchers. Automated end to end test generation, execution, and email based reporting, reducing manual effort and streamlining the testing lifecycle. Developed and tested locally using n8n workflows and agent orchestration
ISTQB Foundation level Certified Tester
Indian Testing Board
June 1, 2026 – Present
Selenium with Java testing
Unknown
June 1, 2026 – Present
Playwright With Javascript Automation testing
Unknown
June 1, 2026 – Present
ISTQB Certified Tester Foundation Level
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including AI-powered test automation generators and AI manual test case generators, shows a strong interest in innovation and advanced QA practices. Their experience across different companies (Andersen Lab, Vanilla Network, Rippey.ai) and roles (Automation QA Engineer, QA Software Tester, QA Engineer, Process Analyst) indicates adaptability and a broad skill set. The focus on AI/ML in QA aligns well with forward-thinking organizations. The candidate's background in technical content writing also suggests strong documentation and communication skills, which are valuable for cultural fit in collaborative environments.
Soft Skills & Operational Fit
The candidate demonstrates strong collaboration skills, working closely with BAs, Developers, Product Owners, and Integration teams. They are adept at participating in sprint planning, backlog refinement, and quality assurance strategy discussions. Their experience with client management, UAT support, and stakeholder communication indicates good operational fit and client-facing abilities. The transition from manual documentation to AI-assisted productivity highlights adaptability and a proactive approach to improving workflows.