Full Description

We are not looking for someone to manage a testing function. We are looking for an engineer who can redefine how quality is engineered into mission-critical banking software. As Lead QA Automation Engineer, you will shape automation architecture, continuous testing, and quality engineering practices for enterprise SaaS platforms used in complex regulated environments. The objective is to move quality upstream using engineering, automation, data, and intelligent tooling to prevent defects rather than simply identify them.

Responsibilities

Define the automation and quality-engineering strategy for complex enterprise banking solutions. Architect scalable automation frameworks across APIs, backend services, integrations, and end-to-end workflows. Embed automated quality gates into CI/CD. Lead API, database, event-driven, and integration testing. Establish engineering metrics that provide meaningful signals about quality and risk. Drive higher levels of intelligent automation and continuous testing. Partner with Engineering, Product, Architecture, and Customer Enablement. Mentor engineers and conduct technical/code reviews. Improve performance, resilience, and scalability testing. Evaluate emerging AI-enabled quality engineering approaches where they demonstrably improve outcomes.

Requirements

Typically 9-12 years in software quality/engineering, with deep automation experience and evidence of having built rather than simply operated automation frameworks. We are particularly interested in engineers from global product companies; fintech/banking technology organizations; banking GCC engineering organizations; high-growth SaaS companies; and engineering cultures such as Microsoft, Salesforce, ServiceNow, Atlassian, Intuit, Red Hat, Nutanix, and comparable organizations. You should bring strong capability across Selenium, Playwright, Cypress, or comparable frameworks; API automation/Rest Assured/Postman; SQL and backend/data validation; CI/CD and continuous testing; Azure DevOps/Jenkins/GitHub Actions; performance engineering; Kafka/event-driven systems; and cloud-native applications, ideally Azure/Kubernetes. The strongest candidates will think like software engineers who happen to specialize in quality. A strong computer science/engineering foundation from a highly regarded institution is preferred, together with evidence of engineering excellence and sustained high performance.