

Experienced in leading quality transformation initiatives, shaping automation strategies that deliver measurable improvements in testing efficiency and coverage. Proven ability to implement AI-driven quality engineering focused solutions.
Helped accelerate Broadridge’s Quality Engineering stream across three strategic pillars: Enterprise Quality Platforms, Test Automation Frameworks, and AI-Driven Quality Engineering Solutions. Responsible for architecting and developing an enterprise-wide Test Harness platform that provides executive visibility into quality, coverage, and other engineering metrics; defining automation framework strategy across UI, API, Database, Cloud, and Desktop technologies; and driving the adoption of Generative AI solutions that accelerate test creation, quality assessment, and engineering productivity.
Framework Strategy & Architecture
• Defined and drove the organization-wide test automation strategy covering UI, API, Database, AWS Cloud, and Desktop application testing via a centralized framework library offering to enable consistent automation implementation across engineering teams.
• Architected solutions leveraging Serenity BDD, Selenium, FlaUI, and custom automation libraries to support diverse testing requirements.
• Designed and implemented a no-code API testing framework, enabling broader adoption of API automated testing across technical and non-technical teams.
• Worked extensively with Jenkins to create standardized test automation execution templates, centralized automation pipelines, and enterprise-scale test orchestration capabilities.
• Provided technical leadership and architectural guidance for framework modernization, automation standards, and quality engineering best practices.
Development & Platform Engineering
• Architected and developed a centralized Enterprise Test Harness application providing executive-level visibility into quality engineering metrics across the organization.
• Designed and implemented scalable REST APIs using Java and Spring Boot to support the app backend.
• Assisted in developing modern user interfaces using ReactJS and Material UI, delivering intuitive dashboards and reporting capabilities for engineering leadership.
• Built integration batch pipeline with Jira, Jenkins, SonarQube, JFrog Xray, Checkmarx, GitLab to pull data for metrics consumption.
• Designed and implemented reusable APIs and services to support AI-driven test generation, test planning, and quality assessment workflows.
AI Innovation & Engineering Productivity
• Architected and developed AI-driven solutions for automated test case generation, test automation code generation, and intelligent test plan creation with Jira integration via Pydantic AI with OpenAI and Claude apis.
• Created an AI-based Jira Story Evaluation service utilizing rule-based guidance and weighted scoring model to assess story readiness and quality; currently piloting to evaluate Sprint Readiness for Jira Stories before dev work starts.
• Built vector embedding-based duplicate test case detection solution, reducing test duplication by more than 50,000 test cases and significantly improving test asset management.
• Created lightweight Jira CLI, reducing token consumption for Jira context and lowering operational overhead compared to MCP-based Jira LLM context libraries.
• Developed evaluation frameworks for AI-powered data chatbot using a fully configuration-driven architecture, enabling scalable and repeatable model assessment.
• Leveraged GitNexus [Code Knowledge Graph], GitLab MCP, Wiz MCP servers for accelerating engineering delivery.
• Championed adoption of Generative AI and intelligent automation across Quality Engineering organization, enhancing overall quality and developer productivity.