Role Overview :

We are looking for an experienced Senior Manager QA/Quality Engineering to lead quality engineering transformation, automation strategy, and delivery across enterprise applications. The ideal candidate should have strong hands-on expertise in Python-based test automation using Playwright, API automation, CI/CD, and modern AI-driven quality engineering practices.

The role will involve building scalable automation frameworks, driving shift-left quality practices, establishing QA standards and KPIs, and leading distributed QA teams while partnering closely with Engineering, Product, and Business stakeholders.

Key Responsibilities :

QA Leadership & Transformation :

- Lead QA and Quality Engineering strategy across multiple projects and products.

- Define and implement scalable QA processes, standards, methodologies, and quality KPIs.

- Drive Shift-Left testing and quality engineering practices across the SDLC.

- Establish automation-first approaches to improve test coverage, release velocity, and product quality.

- Build and evolve QA CoE capabilities, frameworks, reusable accelerators, and best practices.

- Identify opportunities for process optimization, test automation, and intelligent quality engineering.

- Drive root-cause analysis, defect prevention, risk assessment, and continuous improvement.

Test Automation - Python & Playwright:

- Design, develop, and maintain UI automation frameworks using Python and Playwright.

- Establish scalable automation architecture using Page Object Model, reusable components, fixtures, and data-driven approaches.

- Develop automated functional, regression, smoke, and end-to-end test suites.

- Integrate Playwright automation with CI/CD pipelines using GitHub Actions, Jenkins, or Azure DevOps.

- Implement parallel execution, cross-browser testing, reporting, test retry, and flaky-test management.

- Evaluate and modernize existing Selenium-based automation frameworks by introducing Playwright and Python where appropriate.

- Drive automation coverage across critical business workflows and continuously improve automation ROI.

- Establish coding standards, framework guidelines, code reviews, and best practices for automation engineers.

API & Performance Testing:

- Lead API automation using tools such as Python, Postman, RestAssured, or Karate.

- Define API testing strategy covering functional, integration, negative, and contract testing.

- Drive performance testing using JMeter and other appropriate tools.

- Analyze performance bottlenecks and work with engineering teams on remediation.

- Integrate API and performance testing into CI/CD pipelines where appropriate.

AI-Driven Quality Engineering:

- Explore and implement AI/GenAI-assisted testing to improve productivity and test effectiveness.

- Evaluate AI-assisted test generation, test optimization, defect triage, RCA assistance, and regression optimization.

- Define quality validation approaches for AI-powered applications, including:

1. Response accuracy

2. Contextual relevance

3. Response consistency

4. Hallucination detection

5. Prompt effectiveness

6. Edge-case handling

- Participate in designing and validating Agentic AI workflows and autonomous testing solutions.

- Identify opportunities to use tools such as Claude, Cursor, ChatGPT, MCP, and other AI technologies within QA workflows.

CI/CD & Engineering Practices:

- Integrate automated testing into CI/CD pipelines.

- Establish quality gates and automated regression checks within deployment pipelines.

- Work closely with DevOps and Engineering teams to improve continuous testing and release confidence.

- Promote Git-based development, code reviews, test reporting, and engineering best practices.

Team Leadership:

- Lead, mentor, and develop QA/QE engineers across multiple projects.

- Build automation and quality engineering capabilities within the team.

- Conduct technical mentoring, framework reviews, and knowledge-sharing sessions.

- Define team goals, performance expectations, and development plans.

- Manage distributed teams and coordinate with global stakeholders.

Stakeholder Management :

- Partner with Product, Engineering, Business, and Program teams to define quality objectives.

- Own QA strategy, estimates, test plans, release readiness, and quality reporting.

- Communicate quality risks, dependencies, defects, and release recommendations to senior stakeholders.

- Support client discussions, solutioning, proposals, and QA transformation initiatives.

Required Skills & Experience :

- 15+ years of experience in Software Testing / Quality Engineering, with significant experience in QA leadership.

- Strong hands-on experience in Python-based automation.

- Strong expertise in Playwright for web/UI automation.

- Experience designing and implementing automation frameworks from the ground up.

- Strong understanding of Selenium and modern automation framework architecture.

- Experience with API automation and testing.

- Strong experience with CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps.

- Experience with Git and modern software engineering practices.

- Strong understanding of Agile/Scrum, STLC, test strategy, and release management.

- Experience with performance testing, preferably JMeter.

- Experience leading and mentoring QA/QE teams.

- Strong stakeholder management and communication skills.

- Experience working with enterprise/SaaS applications.

Preferred / Good-to-Have Skills :

- Experience in AI/GenAI testing and AI-assisted QA automation.

- Experience with Claude, Cursor, ChatGPT, LLMs, or MCP-based workflows.

- Knowledge of Agentic AI and autonomous workflow validation.

- Experience with AI-assisted test generation and intelligent test optimization.

- Experience with accessibility testing using tools such as NVDA and Axe.

- Experience with web performance tools such as Lighthouse/PageSpeed.

- Banking, Financial Services, Insurance, Payments, or other enterprise-domain experience.

- Experience establishing or scaling a QA CoE / Quality Engineering practice.

Education :

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline.

Key Success Measures :

- Increased automation coverage and reduction in manual regression effort.

- Improved release quality and reduction in production defects.

- Adoption of Python + Playwright automation across strategic applications.

- Improved CI/CD and continuous testing maturity.

- Successful implementation of AI-assisted quality engineering initiatives.

- Strong team capability development and engineering productivity.

- Consistent quality governance, metrics, and stakeholder visibility.