Automation Architect - QE

Job Description

Role Overview: As a Quality Engineer Automation Architect , you will lead the design, implementation, and enhancement of robust automation frameworks to ensure the highest levels of quality in software delivery. This role demands a comprehensive understanding of quality assurance (QA) methodologies, advanced automation tools, and a collaborative approach to mentoring teams and aligning testing strategies with business goals. Key Responsibilities: Automation Framework Development: Design, develop, and maintain scalable, reusable, and robust test automation frameworks. Integrate automation solutions with CI/CD pipelines for seamless deployment. Testing Strategy and Execution: Define comprehensive test strategies, including functional, non-functional, performance, and security testing. Collaborate with cross-functional teams to create detailed test plans and scripts for both frontend and backend systems. Tool Evaluation and Implementation: Evaluate, recommend, and implement modern QA tools and technologies to streamline automation. Ensure tool compatibility with various platforms, applications, and environments. Team Leadership and Mentoring: Guide QA engineers on best practices in test automation and quality engineering. Conduct training sessions to upskill team members on advanced testing tools and techniques. Collaboration: Work closely with developers, product managers, and business stakeholders to align testing processes with business needs. Act as the point of contact for all automation-related activities across projects. Metrics and Reporting: Define and track quality metrics to measure the effectiveness of QA processes. Prepare detailed reports on testing outcomes, automation coverage, and defect trends. Required Skills and Qualifications: Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Architect to own application of AI in QE from conceptualizing, architecting and development. Experience with application of relevant open source AI models in QE. Technical Expertise: Proficiency in at least one programming language (e.g., Java, Python, C#). Hands-on experience with automation tools such as Selenium, Appium, TestNG, JUnit, or similar. Strong knowledge of API testing tools like Postman, RestAssured, or SoapUI. Familiarity with performance testing tools like JMeter or LoadRunner. Expertise in CI/CD tools like Jenkins, GitLab, or Bamboo. QA Methodologies: Deep understanding of Agile/Scrum methodologies and SDLC principles. Experience in testing cloud-based applications and microservices. Soft Skills: Excellent problem-solving, analytical, and troubleshooting skills. Strong written and verbal communication. Ability to lead and inspire cross-functional teams. Preferred Qualifications: Experience with Behavior-Driven Development (BDD) and tools like Cucumber or SpecFlow. Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.