Gagan Pandey

Promoted to Senior SDET / Senior QA Engineer and now leading AI-assisted QA workflows, large-scale automation migration, and cross-functional quality engineering improvements.

• Promoted after consistent delivery in automation strategy, CI/CD quality controls, and cross-functional QA leadership.
• Researched, built POCs, and integrated ChatGPT, Codex, and MCP server workflows across the STLC to improve QA execution quality.
• Implemented AI-assisted test design flows from Jira stories, epics, and Confluence docs, reducing test case creation and automation effort by 70-80%.
• Led migration from Selenium/Selenide (Java/Kotlin) to Playwright with TypeScript across web, mobile, API, kiosk, and desktop testing.
• Migrated 7,500+ test cases, reducing automated execution time by 60% and saving 60% CI time.
• Mentored QA engineers on Playwright/TypeScript standards, test design quality, code reviews, and AI-assisted QA workflows.
• Contributed to ETL/data processing testing using Airflow, Apache Iceberg, Milvus, Spark, and IBM technologies.

Built and scaled automation frameworks across healthcare products while strengthening CI/CD test execution, release readiness, and defect response quality.

• Built and maintained frameworks for web, API, mobile, and application testing using Selenium/Selenide, Java, Kotlin, Appium, WinAppDriver, REST Assured, Postman, JUnit, and TestNG.
• Reduced manual regression effort by 50% through reusable automation utilities and scalable regression coverage.
• Implemented CI/CD test execution in Azure DevOps, GitHub Actions, and GitLab Actions to accelerate feedback and improve release confidence.
• Designed API validation, smoke, regression suites, and release validation checklists for healthcare products.
• Collaborated with product, engineering, R&D, and support teams to reproduce defects, analyze failures, and improve defect resolution efficiency.
• Mentored QA team members on automation best practices, Agile quality execution, and code review quality.

Developed backend and frontend features for the JSIE platform with strong emphasis on API reliability, usability, and production support.

• Developed backend services and RESTful APIs for JSIE using Spring Boot, Groovy, and MongoDB to improve application and data retrieval performance.
• Built Vue.js interfaces and integrated frontend workflows with backend APIs to improve usability and platform engagement.
• Participated in Agile ceremonies, sprint planning, code reviews, documentation, and post-release support.
• Monitored application behavior after launch, investigated issues, and supported defect fixes for reliable operations.
• Collaborated with clients and stakeholders to clarify requirements and deliver user-focused software features.