Quality Assurance (QA) Engineer

We are seeking a highly skilled and innovative Quality Assurance Professional to join our dynamic technology team. The ideal candidate will ensure software quality across diverse technological domains, including web, mobile, AI-driven applications, data science platforms, and robotic process automation (RPA) solutions. Key Responsibilities: • Design, develop, and execute comprehensive test cases and test plans for: o Web and mobile applications o AI and machine learning models o Data science platforms o Robotic process automation workflows • Conduct thorough manual and automated testing across multiple platforms and technologies • Create detailed bug reports and track issues through complete resolution lifecycle • Collaborate closely with cross-functional teams including development, data science, and AI engineering groups • Develop and maintain automated test scripts using industry-standard tools • Perform regression, functional, performance, and user acceptance testing • Test AI model performance, fairness, and accuracy • Assess data pipeline integrity and ETL process reliability • Verify RPA workflow effectiveness and efficiency • Participate in Agile methodology sprint planning and continuous improvement initiatives Technical Skills Required: • Testing Methodologies: Functional, Regression, Performance, User Acceptance, AI/ML Model Validation, Data QA, RPA Workflow Testing • Automation Tools: Selenium WebDriver, Appium, JUnit, TestNG, Cucumber, UiPath Test Suite, Blue Prism, Automation Anywhere • Bug Tracking/Management: JIRA, Confluence, Azure DevOps, TestRail, qTest • Programming/Scripting: Java, Python, SQL, R, JavaScript • Web/Mobile Testing: Android Studio, XCode, Firebase Test Lab, Chrome DevTools, BrowserStack • AI/Data Science Testing: TensorFlow, PyTest, AI Fairness 360, Apache Spark, Pandas, NumPy, Scikit-learn • Performance Tools: JMeter, Gatling, LoadRunner, K6 • CI/CD and Cloud Platforms: Jenkins, GitLab CI, GitHub Actions, AWS, Azure, Google Cloud Required Qualifications: • Bachelor's degree in Computer Science, Information Technology, or related field • 3-5 years of professional QA experience • Strong understanding of software development lifecycle (SDLC) • Proven experience in testing diverse technological ecosystems Preferred Certifications: ISTQB Certified Tester, Certified Software Quality Analyst (CSQA), AI/ML Testing Specialized Certifications Advanced Competency Areas: • AI Model Performance Validation: Proficient in evaluating machine learning models to ensure accuracy, robustness, and reliability under diverse scenarios. • Algorithmic Bias Mitigation: Skilled in identifying and addressing biases within AI systems to promote fairness and inclusivity in outputs. • Data Pipeline Integrity: Expertise in validating ETL processes and ensuring seamless, error-free data flow across pipelines. • Workflow Automation Testing: Adept at assessing complex automated workflows to ensure accuracy, reliability, and operational efficiency. • Performance Optimization: Capable of analyzing and enhancing software performance through scalable and resource-efficient strategies. • Security and Compliance: Well-versed in testing applications to meet stringent security standards and compliance with data protection regulations. • Intelligent Automation Validation: Experienced in evaluating RPA solutions and intelligent automation tools to ensure they meet functional and business requirements. • Machine Learning Accuracy: Competent in validating the precision and reliability of machine learning models in real-world and test-case scenarios. • Data Science Platform Reliability: Skilled in testing the stability, scalability, and performance of data science platforms across varied use cases. • RPA Workflow Efficiency: Proficient in verifying robotic process automation workflows for alignment with organizational objectives and operational efficiency. • AI System Fairness and Transparency: Expertise in ensuring AI systems adhere to ethical guidelines, operate transparently, and produce explainable, unbiased outcomes.