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Anjana Kulasinghe ( AJ )
Lead Test Automation Consultant
Modern Quality Engineering with AI-Assisted Practices
Download CV
Lead Test Automation Consultant
Modern Quality Engineering with AI-Assisted Practices
Download CVWith over 16 years of experience in the IT industry, I’ve built a career focused on software quality, automation excellence, and pragmatic engineering practices. My journey began with hands-on manual testing and evolved into designing and delivering scalable, enterprise-grade test automation frameworks that reduce risk, cost, and time-to-market.
I am an experienced engineer who selectively applies AI-assisted tools such as GitHub Copilot, ChatGPT, Claude, and Gemini to remove repetitive effort, speed up analysis, and improve test design. AI is used as an accelerator, while architectural decisions, engineering judgement, and accountability always remain human-led.
An Agile/Scrum practitioner and mentor, I enjoy guiding teams, shaping quality strategies, and improving engineering maturity through automation, data-driven insights, and thoughtful use of modern tooling.
Designing and building robust, maintainable test automation frameworks using Selenium, Appium, and modern testing tools. Focused on end-to-end automation solutions that improve confidence, reduce manual effort, and scale with delivery needs.
Delivering practical performance and load testing using JMeter and Neustar to validate system behaviour under real-world conditions and identify performance risks early.
Establishing effective QA strategies, governance, and mentoring practices to embed quality into delivery pipelines and ensure consistent, reliable outcomes.
Using tools such as GitHub Copilot and intelligent IDE assistants to accelerate development and refactoring, improve test consistency, and reduce repetitive engineering work while keeping design and decision-making human-led.
Hands-on experience using LLM-based assistants (ChatGPT, Claude, Gemini) to support test design, result analysis, documentation, and problem-solving through structured, intentional prompting.
Applying AI-assisted techniques for Test design support, Automated test data generation, API test analysis, Faster defect investigation and root-cause analysis. Used to support testing decisions, not replace engineering judgement.
“ My goal is to help teams evolve from Automation-Enabled Delivery to AI-Assisted, Judgement-led Quality Engineering. ”
Ready to discuss your next project or explore collaboration opportunities? I'd love to hear from you and discuss how we can work together to achieve excellence in quality assurance and test automation.