Sr. Principal, Quality Engineering Architect
New
Remote-first flexibility within IndiaFull-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- PythonCypressJavaJavascriptSeleniumCI/CDDevOpsGenerative AIPlaywright
Requirements
- 10+ years of experience in software quality engineering with strong expertise in test automation architecture for enterprise-scale systems.
- Proven experience designing AI-powered or advanced automation frameworks using tools such as Playwright, Selenium, Cypress, and REST Assured.
- Strong programming skills in Python, Java, or JavaScript with the ability to build scalable automation and AI-driven testing solutions.
- Hands-on experience integrating AI/ML concepts such as generative AI for test case generation, defect analysis, and test data creation.
- Deep understanding of CI/CD pipelines, DevOps practices, and cloud-native environments (AWS, Azure, or GCP).
- Experience with observability tools, data-driven testing, and analytics-based quality decision-making.
- Familiarity with MLOps concepts, including model validation, drift detection, and AI system testing.
- Strong leadership, communication, and stakeholder management skills with the ability to influence engineering direction.
- Bachelor’s degree in Computer Science or equivalent technical discipline.
Responsibilities
- Lead the architecture and design of AI-driven quality engineering frameworks across UI, API, data, and microservices ecosystems, ensuring scalability, reusability, and enterprise readiness.
- Develop and implement intelligent automation solutions that reduce manual testing effort through AI agents for test generation, execution optimization, and defect analysis.
- Embed AI capabilities into CI/CD pipelines by defining smart quality gates, predictive testing models, and automated feedback loops.
- Design advanced test infrastructure including test harnesses, mock services, and synthetic data generation frameworks to support continuous validation.
- Drive adoption of modern engineering practices such as BDD, TDD, observability-driven testing, and risk-based quality strategies.
- Provide technical leadership across performance, security, scalability, and resilience testing within complex distributed systems.
- Mentor engineering teams and establish governance standards for automation frameworks, coding practices, and AI-enabled QA adoption.
- Collaborate with product and engineering stakeholders to define test strategies, improve testability, and align quality goals with delivery objectives.
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