Results-driven Automation Test Lead and Quality Engineering professional with 13+ years of experience delivering large-scale digital transformation, banking, wealth management, fintech and energy programs across Australia. Proven expertise in leading automation transformation initiatives, building enterprise-grade automation frameworks, implementing shift-left quality practices and integrating automated testing into CI/CD pipelines. Strong hands-on experience with Playwright, Selenium, API testing, Tricentis Tosca, Azure DevOps and Agile delivery. Experienced in AI-assisted testing, LLM-driven test design, prompt engineering, AI-powered defect triage and intelligent test automation solutions. Recognized for driving quality engineering excellence, mentoring teams and reducing release risk while accelerating software delivery.
KEY ACHIEVEMENTS
• Member of the Automation Governance Authority (AGA) at National Australia Bank, defining enterprise-wide test automation standards, frameworks, and quality governance.
• Led automation transformation initiatives across multiple programs, improving test efficiency, scalability, and maintainability.
• Reduced regression execution time by 70% through automation of critical business workflows and CI/CD integration.
• Established shift-left testing practices using API virtualization, service mocking (WireMock), and early quality engagement.
• Increased automation coverage across UI, API, integration, and end-to-end testing layers, improving release confidence.
• Introduced AI-assisted testing solutions leveraging GitHub Copilot, GenAI, and intelligent test design techniques.
• Improved defect detection and reduced production incidents through risk-based testing and quality engineering practices.
• Performed SQL and data validation testing to ensure data accuracy, integrity, and compliance.
• Led defect triage, root cause analysis (RCA), and production support activities for critical releases.
• Produced quality metrics, test dashboards, governance reports, and audit evidence for executive stakeholders.
RESPONSIBILITIES
• Lead end-to-end Test Delivery across manual and automation testing streams for enterprise applications.
• Define test strategy, test plans, quality gates, and release readiness criteria.
• Design, develop, and maintain scalable automation frameworks using Playwright, Selenium, WebdriverIO, JavaScript, and TypeScript.
• Drive functional, integration, API, system, regression, UAT, and end-to-end testing activities.
• Lead test estimation, resource planning, risk management, and stakeholder communication.
• Review test artefacts, automation code, and testing deliverables to ensure quality standards.
• Collaborate with Product Owners, Architects, Developers, Business Analysts, and Delivery Leads.
• Manage test environments, test data, defect management, and release coordination activities.
• Integrate automated testing into CI/CD pipelines using Azure DevOps, GitHub Actions, and Harness.
• Mentor QA engineers and promote quality engineering, DevOps, and shift-left testing practices.
• Drive continuous improvement initiatives across test processes, automation frameworks, and delivery practices.
• Support performance, API, database, ETL, and microservices testing across cloud-native platforms.
• Led the design, development, and continuous enhancement of enterprise test automation frameworks using Selenium, C#, and industry best practices.
• Defined automation strategy, roadmap, and regression testing approach to improve coverage, efficiency, and release quality.
• Managed test estimation, planning, resource allocation, and delivery across multiple projects and releases.
• Provided quality governance, stakeholder reporting, and executive-level communication on testing progress, risks, and release readiness.
• Facilitated defect triage, root cause analysis (RCA), risk assessment, and resolution management across cross-functional teams.
• Led end-to-end testing activities, including functional, integration, system, regression, UAT, and production release validation.
• Mentored and coached QA engineers, driving technical excellence, automation adoption, and quality engineering best practices.
• Collaborated with Product Owners, Business Analysts, Developers, Architects, and Delivery Managers to align testing strategies with business objectives.
• Analyzed test results, quality metrics, and defect trends to provide actionable insights and support informed release decisions.
• Drove continuous improvement initiatives by optimizing testing processes, automation frameworks, test coverage, and delivery efficiency.
• Established quality gates and governance controls to ensure consistent testing standards across projects.
• Integrated automated testing into CI/CD pipelines, enabling faster feedback loops and supporting DevOps practices.
Projects: NAB, EnergyAustralia
Project: Prosper
Prosper is America's first peer-to-peer lending marketplace, with more than 2 million members and over $6 billion in funded loans. It handles the servicing of the loan on behalf of the matched borrowers and investors.
Projects: MUFG Bank
MUFG is one of the world's leading financial groups. Headquartered in Tokyo. Confidential is a global network offering services including commercial banking, trust banking, securities, credit cards, consumer finance, asset management, and leasing.
· Designed and implemented E2E evaluation suites for LLM based AI agents using DeepEval, covering tool correctness, task completion, prompt alignment and step efficiency metrics.
· Built RAG pipeline evaluation covering hallucination detection(Faithfulness metric), retrieval ranking quality(Contextual precision) and retrieval coverage(Contextual recall) using GPT-4o as judge LLM.
· Evaluated multi turn chatbot conversations using ConversationalTestCase with KnowledgeRetention, TurnRelevancy and ConversationalCompleteness metrics to catch memory failures and role breaks across turns.
· Implemented safety evaluation suite covering Bias, Toxicity and PII leakage on a live support agent using DeepEval's synthesizer to auto-generate test inputs directly from policy documents.
· Instrumented LangChain agents with DeepEval tracing(@observe, CallbackHandler, update_current_trace) to capture tool calls, LLM spans and retrieval context for metric evaluation without modifying agent logic.
· Authored custom evaluation criteria using GEval and conversationalGEval to assess domain-specific quality dimensions beyond pre-built metrics.
Australian Citizen