Irfan Shaik

About Irfan Shaik

QA Automation Engineer with 4+ years of experience delivering high-quality, scalable software solutions across web, mobile, and cloud platforms. I specialize in building robust automation frameworks and driving end-to-end testing strategies that improve product reliability, reduce release cycles, and enhance user experience. Proficient in modern automation tools including Selenium, Playwright, Cypress, and Appium, with strong programming expertise in Python and JavaScript. Experienced in API testing, microservices validation, AI model testing, and performance engineering, with hands-on exposure to cloud platforms such as AWS and Azure. At Mastercard, I contributed to an AI-driven fraud detection platform, achieving 92% automation coverage and 98% test coverage while improving testing efficiency and ensuring regulatory compliance. I collaborate closely with cross-functional Agile teams to design test strategies, manage defects, and support continuous integration and delivery pipelines. I am passionate about quality engineering, continuous improvement, and leveraging automation and AI to build reliable and secure systems. I thrive in fast-paced environments where innovation, collaboration, and data-driven decision-making are key. Core Focus Areas: • Test Automation & Framework Development • API & Microservices Testing • AI/ML Model Validation • Performance & Security Testing • CI/CD & DevOps Integration • Cloud-based Testing (AWS, Azure)

Experience

1. Qa Automation Tester

   Mastercard

   Jul 2023 — Present · US

   Executed end-to-end QA for Project AI-Guard, an AI-driven fraud detection platform, collaborating with developers, analysts, and compliance teams, creating detailed test strategies, traceable test cases, and regulatory documentation, achieving 98% test coverage across all modules.• Developed automated test scripts using Selenium and Python frameworks, integrated with TestNG and Jenkins pipelines, performing functional, regression, and integration testing, reducing testing cycle time by 15% and achieving 92% automation coverage across core platform functionalities.• Performed cross-platform testing on web and mobile applications hosted on AWS Cloud, validating performance, load, and security compliance while coordinating with DevOps teams, identifying and resolving 87% of critical defects prior to production release.• Validated AI-powered fraud detection algorithms with real transaction datasets using SQL queries and Python scripts, ensuring 95% prediction precision, collaborating with data scientists, refining test scenarios, and performing exploratory and regression testing for robust model validation.• Monitored production releases, conducted user acceptance and security testing, maintained detailed QA reports, leveraged Agile and Scrum methodologies, collaborated with stakeholders, achieving 99% post-release defect-free rate while ensuring scalable and compliant cloud infrastructure readiness.• Optimized test coverage by using constant integration and delivery pipelines, integrating Selenium, Jenkins, Git, and TestRail, executing API and performance tests, documenting findings, improving test efficiency and supporting end-to-end system reliability across multiple environments.

Education

• Saint Peter's University

  Master of Science, Data Science

• Pace Institute of Technology & Sciences

  Bachelor of Technology, Computer Science Engineering