Lead Software Quality Engineer (AI Testing)

MALATHI YANNAM

LEAD SOFTWARE QUALITY ENGINEER

*******.*****@*****.*** 480-***-****

EXECUTIVE SUMMARY

Lead Software Quality Engineer with 11+ years of experience in Data Quality Testing Test Automation, API Testing, Data Validation,ETL/ELT validation, data pipeline testing, and AI-driven application testing across the Higher Education and Banking domains.

Leveraged Claude AI and Claude Code to accelerate test design, automation development, debugging, and defect analysis across functional, regression, API, and database testing.

Expertise in leveraging Claude AI/Claude Code to review automation code, identify potential defects and edge cases, assess regression risks, and enhance overall test coverage and automation quality.

Extensive experience designing and executing comprehensive test strategies, test plans, test cases, regression testing, functional testing, integration testing, system testing, UAT support, and end-to-end validation for enterprise applications.

Strong hands-on experience with Databricks, advanced SQL, and Python for validating large-scale enterprise datasets, performing source-to-target reconciliation, data profiling, transformation validation, and anomaly detection

Expertise in designing and maintaining automation frameworks using Selenium WebDriver, Java, REST Assured, Postman, TestNG, Maven and advanced XPath strategies for functional, regression, API, and end-to-end testing, improving test coverage and release quality.

Strong understanding of Databricks Lakehouse architecture, ETL/ELT workflows, AWS cloud environments, and enterprise data warehousing.

Experienced in defect management, root-cause analysis, data reconciliation, and collaborating with data engineers, developers, business analysts, and product teams to identify and remediate data-quality issues.

Experienced in Generative AI, Large Language Model (LLM), and Agentic AI application testing, validating AI-generated responses, agent behavior, workflow execution, reliability, and end-to-end application quality.

Experience in test automation using Playwright with Python, developing reusable and maintainable automated test scripts for UI, functional, regression, and end-to-end testing across multiple browsers.

Experience validating LangChain and LangGraph-based AI workflows, including prompt execution, chain orchestration, agent decision-making, tool invocation, state transitions, and end-to-end workflow behavior.

Proven expertise in SQL, database testing, data reconciliation, source-to-target validation, Power BI, Excel, and data analytics, validating large-scale academic, financial, and enterprise datasets across reporting and analytical platforms.

Developed and maintained API automation test scripts using the Karate Framework for RESTful web services. Generated and reviewed Karate test execution reports and communicated automation results to project stakeholders.

Experienced in testing Degree Progress Audit (DPA), Student DPA, What-If Analysis, Traditional Academic Planning, and AI-enabled Data Analytics platforms within Higher Education.

Strong understanding of Agile Scrum, SDLC, STLC, defect life cycle, release management, risk assessment, and quality assurance best practices, collaborating effectively with cross-functional teams.

Skilled in working closely with Product Owners, Business Analysts, Developers, Data Engineers, Architects, and Business Stakeholders to analyze requirements, refine user stories, define acceptance criteria, and deliver high-quality software.

Experienced in creating and validating Power BI dashboards, SQL reports, and business intelligence solutions to support data-driven decision-making.

Hands-on experience with Databricks, Azure Data Lake Storage (ADLS), and Snowflake for validating data pipelines, analytical workflows, data transformations, and reporting datasets.

Demonstrated leadership in mentoring QA engineers, leading automation initiatives, improving testing processes, coordinating defect resolution, and driving continuous quality improvements across Agile delivery teams.

Skilled in defect management and release coordination using JIRA and Azure DevOps, driving timely resolution of critical issues across sprint cycles.

Proficient in CI/CD integration for automated test suites using Jenkins and GitHub Actions, streamlining build validation and reducing release cycle time.

Hands-on experience with ADA/WCAG accessibility testing, validating web applications against accessibility standards using JAWS and NVDA screen readers, along with keyboard navigation and accessibility verification techniques.

Excellent analytical, problem-solving, communication, stakeholder management, and documentation skills with a proven ability to deliver high-quality solutions in fast-paced Agile environments.

PROFESSIONAL EXPERIENCE

Data AI – AI-Driven Data Analytics & Validation Platform Jan 2026 – Present

Employer: EXL Services, USA Role: Lead Software Quality Engineer

Technologies/Tools: Claude AI, Generative AI (GenAI), Prompt Engineering, SQL, Play Wright, Data bricks, ETL Strategies,AWS,Postman, Power BI, Data Profiling, Azure DevOps, AI/ML Validation, Anomaly Detection

The Data AI platform is an enterprise data analytics and AI validation initiative built for Vectra Bank to support data-driven decision-making across banking and financial reporting functions. The platform leverages Databricks-based data pipelines, machine learning models, and predictive analytics to generate business intelligence insights, automate enterprise reporting workflows, and validate financial data in near real time across multiple internal systems. As Lead Software Quality Engineer, owned the end-to-end quality strategy covering AI/ML model validation, backend data integrity, API testing, data pipeline validation, and enterprise reporting accuracy.

Responsibilities:

Used Claude Code with Python, Playwright, Pytest, and Page Object Model (POM) to assist in developing, reviewing, refactoring, and maintaining scalable and reusable automated regression test suites.

Leveraged Claude AI to analyze Playwright execution failures, error messages, logs, screenshots, traces, and stack traces to accelerate root-cause analysis and troubleshooting.

Experienced in leveraging GitHub Copilot and AI-assisted development capabilities to accelerate automation script development, code review, test-case generation, debugging, refactoring, and maintenance of automated regression suites.

Developed data-driven and parameterized Playwright tests to validate multiple business scenarios and datasets while maximizing automation code reuse. .

Developed and executed comprehensive data quality and ETL/ELT test strategies for large-scale enterprise data pipelines running on Databricks.

Experienced in incorporating AI-assisted capabilities into DevOps and CI/CD workflows to improve automation development, troubleshooting, pipeline efficiency, and overall software delivery quality.

Performed extensive SQL-based data validation to verify source-to-target mappings, transformation logic, record counts, aggregations, joins, referential integrity, duplicates, null values, and business rules.

Performed data profiling to identify data patterns, distributions, nulls, duplicates, outliers, invalid values, and inconsistencies before and after ETL/ELT processing.

Performed anomaly detection by analyzing unexpected changes in record counts, data distributions, values, trends, and transformation outputs.

Led end-to-end quality assurance activities for AI-driven data analytics applications, enterprise reporting platforms, and data validation solutions.

Validated AI/ML model outputs, inference results, predictive analytics, and business intelligence reports to ensure accuracy, consistency, and compliance with business rules.

Executed source-to-target validation, data reconciliation, and database testing using complex SQL queries to ensure data integrity across multiple enterprise systems.

Validated ETL pipelines, data transformations, aggregations, calculations, and business rule implementations within large-scale analytical platforms.

Designed and executed API test cases using Postman to validate request/response payloads, authentication mechanisms, and data contracts between AI services and downstream systems.

Validated data pipelines and datasets deployed within AWS-based cloud environments, including integration between cloud data services and Databricks.

Collaborated with Product Owners, Business Analysts, Data Scientists, Data Engineers, and Development teams to review requirements, refine user stories, and validate acceptance criteria.

Designed and executed functional, regression, integration, system, and end-to-end test scenarios for data-intensive applications.

Performed backend data validation using SQL, ensuring completeness, consistency, and accuracy of high-volume datasets.

Verified Power BI dashboards and reports by validating underlying datasets, calculations, filters, and key business metrics.

Managed defects, coordinated defect triage meetings, and tracked releases using Azure DevOps.

Participated in Agile Scrum ceremonies including Sprint Planning, Daily Stand-ups, Sprint Reviews, Retrospectives, and Backlog Refinement.

Worked closely with cross-functional teams to identify risks early, improve testing efficiency, and mentor junior QA engineers on AI validation techniques and automation best practices.

Degree Progress Audit (DPA) Sep 2022 – Dec 2025

Employer: EXL Services, USA Role: Lead Software Quality Engineer

Technologies/Tools: Claude AI, Claude Code, Generative AI (GenAI), AI-Assisted Testing, Selenium WebDriver, Play Wright, Postman, Python, Data bricks, SQL, Power BI, Jenkins, JIRA, Git, Agile Scrum, Karate

Degree Progress Audit (DPA) is an enterprise academic planning and evaluation platform used to assess student academic records, completed coursework, transfer credits, GPA calculations, degree requirements, and graduation eligibility.

Responsibilities:

Leveraged Claude for REST API testing, including generating test scenarios, analyzing JSON request/response payloads, validating API behavior, and identifying negative and boundary test conditions.

Applied AI-assisted techniques to analyze test failures, execution logs, stack traces, and automation errors, accelerating root-cause analysis and distinguishing application defects from automation, test-data, and environment issues.

Tested Databricks notebooks, jobs, workflows, Delta tables, and data transformation pipelines to ensure data accuracy and processing reliability.

Led the design, enhancement, and maintenance of Selenium WebDriver automation frameworks, establishing reusable automation components and expanding regression coverage across enterprise application releases.

Developed and maintained robust XPath expressions using relative XPath, dynamic XPath, XPath functions, axes, and attribute-based strategies to identify complex and dynamic web elements for Selenium and Playwright automation.

Created reusable Karate feature files and scenarios using Gherkin syntax

Used Python for API response validation, JSON processing, data comparison, and backend verification.

Performed backend SQL validation and source-to-target reconciliation to verify academic data integrity, mapping accuracy, calculated results, and business-rule compliance across DPA workflows.

Utilized GitHub Copilot to assist with test scenario development, code reviews, identification of edge cases, and creation of reusable automation functions while reviewing AI-generated code for accuracy and alignment with automation standards.

Validated end-to-end DPA business workflows, including academic records, completed coursework, transfer credits, GPA calculations, degree requirements, and graduation eligibility across supported academic scenarios.

Validated Power BI dashboards and reports against underlying SQL datasets, verifying calculations, filters, KPIs, and business metrics for accuracy and consistency.

Partnered with Product Owners, Business Analysts, and development teams to analyze requirements, identify testable acceptance criteria, clarify business rules, and ensure comprehensive coverage of DPA functionality.

Contributed to Agile Scrum planning and refinement activities, providing QA estimates, identifying testing dependencies, reviewing acceptance criteria, and communicating quality risks throughout sprint execution.

Managed JIRA defect life cycle activities, supporting root-cause analysis, prioritization, retesting, and closure while coordinating with developers to resolve critical issues before release.

Integrated Selenium automation suites with Jenkins CI/CD workflows, supporting automated build validation and maintaining test assets through Git-based source control.

Conducted cross-browser and regression test cycles prior to each release to validate application stability across supported environments.

Prepared test plans, test cases, automation scripts, test execution reports, defect reports, and quality metrics to support enterprise software releases.

Student DPA (Degree Progress Audit) July 2018 – Aug 2022

Employer: Clairvoyant, USA Role: Software Quality Engineer

Technologies/Tools: Selenium WebDriver, Java, SQL, Postman, Azure DevOps, Power BI, JIRA, Agile Scrum, REST API Testing, NVDA

Student Degree Progress Audit (DPA) is an academic planning and evaluation platform used to assess student degree progress, completed coursework, credit requirements, GPA calculations, and graduation eligibility across traditional and non-traditional academic programs.

Responsibilities:

Analyzed business requirements, functional specifications, and academic program rules to identify test conditions, define acceptance coverage, and develop comprehensive functional and regression test scenarios.

Executed end-to-end validation of Student Degree Progress Audit (DPA) workflows across Traditional and Non-Traditional academic programs, verifying academic rules, calculations, and user-facing outcomes.

Validated student academic records, completed coursework, credit hours, GPA calculations, and degree-progress results, ensuring consistency between business rules and application outputs.

Validated student-facing dashboards and academic progress displays, verifying remaining credits, graduation status, completed requirements, and consistency with backend student data.

Created relative and dynamic XPath expressions using element attributes, text, partial attribute values, and DOM relationships to improve automation reliability

Executed SQL queries for backend data validation and reconciliation, verifying student academic records and ensuring database results aligned with expected DPA calculations.

Performed ADA/WCAG accessibility testing to validate web applications by using NVDA for accessibility and usability by users with disabilities.

Validated accessibility requirements against WCAG guidelines and documented accessibility defects with clear reproduction steps, severity, user impact, and recommended remediation.

Executed functional and regression test cycles for new DPA enhancements, validating new functionality while protecting existing academic-planning workflows.

Logged and managed JIRA defects, performed retesting of resolved issues, and collaborated with developers to verify fixes and support defect closure.

Collaborated with Business Analysts and Developers to clarify requirements and validate acceptance criteria for new user stories.

Supported User Acceptance Testing (UAT) by coordinating with business stakeholders and addressing feedback prior to production releases.

Documented test results, prepared status reports, and maintained test case repositories to support audit and compliance requirements.

Hypothetical Audit (What-If Analysis) June 2015 – June 2018

Employer: Clairvoyant, USA Role: Software Quality Engineer

Technologies/Tools: REST API Testing, Postman, SOAP UI, JIRA, Agile Scrum.JAWS

Hypothetical Audit is an academic planning and What-If Analysis application that enables users to evaluate program changes, compare degree requirements, assess course and credit transfers, and determine graduation eligibility based on alternate academic paths.

Responsibilities:

Designed and executed functional and integration test scenarios based on academic business rules, covering program changes, course transfers, degree requirements, and eligibility calculations.

Validated What-If Analysis workflows used for academic planning and program comparison, ensuring application results accurately reflected selected program changes.

Conducted screen-reader testing using JAWS to verify page content, headings, links, buttons, form fields, labels, error messages, and interactive components were correctly announced and accessible.

Tested program-switching functionality to ensure accurate transfer of courses, credits, and degree requirements between programs.

Validated academic evaluation rules and graduation-eligibility calculations across alternate program scenarios, ensuring results remained consistent with defined academic requirements.

Designed and executed REST API and SOAP web-service test scenarios using Postman and SOAP UI, validating service responses, data accuracy, and integration behavior across academic workflows.

Worked closely with Business Analysts, Developers, and QA teams to ensure successful delivery of high-quality releases.

Managed defects in JIRA and participated in Agile Scrum development processes.

TECHNICAL SKILLS

Key Skills: Quality Assurance (QA), Test Automation, API Testing, Data Validation, Data Quality Testing, Source-to-Target Validation, Data Reconciliation, AI-Driven Testing, Agile Testing, User Acceptance Testing (UAT), Regression Testing

Databases: SQL, Oracle, SQL Server, MySQL, Snowflake

AI/GenAI: Claude AI, Claude Code, Generative AI, Prompt Engineering, AI-Assisted Testing

Cloud & Data Analytics Platforms: Databricks, Microsoft Fabric, Azure Data Lake Storage (ADLS), Snowflake

Tools & Technologies: Selenium WebDriver,Play Wright,Java, Python, Postman, REST Assured, SOAP UI, TestNG, Maven, Power BI, Azure DevOps, Jenkins, GitHub Actions, Git, JIRA

Operating Systems: Linux, Windows

Testing Expertise: Functional Testing, System Testing, Integration Testing, Regression Testing, User Acceptance Testing (UAT), ETL Testing, Big Data, API Testing, End-to-End Testing

AI/ML & Data Analytics: AI-Driven Application Testing, Machine Learning Model Validation, Inference Testing, Predictive Analytics Validation, Data Pipeline Verification, AI/ML Output Validation

CI/CD & DevOps: Jenkins, GitHub Actions, Azure DevOps, Git

Accessibility Testing: ADA/WCAG Testing, JAWS, NVDA, Keyboard Accessibility Testing, Screen Reader Testing

Methodologies: Agile Scrum, Waterfall, Software Development Life Cycle (SDLC), Software Testing Life Cycle (STLC)

Reporting & Visualization: Power BI, Microsoft Excel, Dashboard Validation, Analytics Reporting

EDUCATION & CERTIFICATIONS

Education

Master's in Computer Applications (MCA)

Osmania University, India

Certifications

Professional Scrum Master II (PSM II)

Professional Scrum Product Owner II (PSPO II)

Certified SQL Developer

Contact this candidate