• Designed and developed test frameworks for various components within the AI assistant architecture using gRPC and REST API

• Built an end-to-end Android automation test .famework in Python with AI integration, significantly enhancing QA team productivity.

• Created comprehensive test cases for NLU testing using LLM-based AI models, aligned with product requirements.

• Developed an internal web application tool for developers and management to visualize test results effectively, facilitating the identification of underperforming components.

• Conduct automated and E2E manual testing on various devices including mobile, speaker, tv, watch, and fridge on production and QA environments

• Write test plans and test cases based on product requirement documents and execute them and log defects

• Lead a team to triage reported issues and file bug reports to ensure quick analysis/bug fixes from developers.

• Develop robust automation testing frameworks using nodejs along with various libraries such as webdriverio (selenium webdriver), chai, mocha

• Develop new testing techniques/methods and providing process improvement recommendations

• Work closely with the data science team within an agile process to test the new features of the natural language system

• Develop a testing tool using React/Redux to help test AI’s natural language classification

• Reproduce bugs and provide necessary information for developers to triage/fix bugs

• Participate in regression testing for new releases

• Create a chrome extension to scrape web pages to filter out newly created tickets and update to google spreadsheets using the google api, reducing time spent on updating the google spreadsheet by 80%.