Principal Quality Engineer (AI Automation Architect)

As a Principal Quality Engineer (AI Automation Architect) at EquiLend in Bengaluru, you will be responsible for owning and driving the AI strategy, architecture, and adoption for test automation across the organization. Your role will involve collaborating with quality engineers, Engineering, Product, and DevOps teams to enhance automated testing processes using AI technology. Key Responsibilities: - Own the end-to-end AI test automation architecture, including approved tools and models integration with the QE technology stack. - Define how AI-assisted workflows connect with various testing tools like Selenium, Playwright, Cucumber, and CI/CD pipelines. - Establish mandatory human review points for AI-assisted test design, automation code, test data, documentation, and reporting outputs. - Maintain a roadmap tracking industry changes and translate them into quality engineering patterns. - Define and maintain QE standards, including library prompts, repository templates, agent skills, naming conventions, and quality gates. - Set data-handling guardrails to protect sensitive information in AI-assisted workflows. - Build and enhance AI-enabled QE capabilities like intelligent test generation, automation code generation, and failure analysis. - Integrate AI workflows into CI/CD pipelines and QE tooling for streamlined processes. - Train and coach quality engineers on effective AI use and human-in-the-loop review for AI-generated tests. - Partner with product and engineering teams to ensure AI-assisted quality engineering supports reliable delivery. Qualifications Required: - 12+ years' experience in software quality, test automation, QE platform engineering, or similar roles with 3+ years influencing automation strategy at scale. - Practical experience in using LLMs and AI coding agents in quality engineering workflows. - Hands-on experience with modern test automation tools such as Playwright, Selenium, Cypress, BDD, Cucumber, and CI/CD. - Experience with agentic IDEs, Copilot-class tools, and custom agent skills for automation. - Track record of architecting multi-product quality engineering programs and supporting multiple product teams. - Strong understanding of reviewing and validating AI-generated tests, code, and documentation. - Knowledge of Agile or Scrum delivery practices and good analytical skills. - Clear communication skills to coach engineers and influence adoption across Agile teams. EquiLend is a global financial technology firm specializing in the securities finance industry. They provide infrastructure for trading, managing, and reporting for financial institutions worldwide. Their products include trading platforms, market intelligence, RegTech solutions, and Clearing Services. EquiLend operates globally, focusing on efficiency, transparency, and automation in the securities finance lifecycle. If you join EquiLend, you can expect recognition for your contributions, flexible remote working options, generous annual leave, comprehensive health insurance, personal accident insurance, annual team retreats, and relocation support if needed. EquiLend values diversity and inclusion, aiming to create a workplace where everyone feels welcome and supported. They actively work towards building diverse teams to bring different perspectives and ideas to the table. If you require any accommodations during the recruitment process, EquiLend is committed to working with you to make it happen. As a Principal Quality Engineer (AI Automation Architect) at EquiLend in Bengaluru, you will be responsible for owning and driving the AI strategy, architecture, and adoption for test automation across the organization. Your role will involve collaborating with quality engineers, Engineering, Product, and DevOps teams to enhance automated testing processes using AI technology. Key Responsibilities: - Own the end-to-end AI test automation architecture, including approved tools and models integration with the QE technology stack. - Define how AI-assisted workflows connect with various testing tools like Selenium, Playwright, Cucumber, and CI/CD pipelines. - Establish mandatory human review points for AI-assisted test design, automation code, test data, documentation, and reporting outputs. - Maintain a roadmap tracking industry changes and translate them into quality engineering patterns. - Define and maintain QE standards, including library prompts, repository templates, agent skills, naming conventions, and quality gates. - Set data-handling guardrails to protect sensitive information in AI-assisted workflows. - Build and enhance AI-enabled QE capabilities like intelligent test generation, automation code generation, and failure analysis. - Integrate AI workflows into CI/CD pipelines and QE tooling for streamlined processes. - Train and coach quality engineers on effective AI use and human-in-the-loop review for AI-generated tests. - Partner with product and engineering teams to ensure AI-assisted quali