InfoBeans Technologies - Senior Manager - Quality Engineering

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 accuracy2. Contextual relevance3. Response consistency4. Hallucination detection5. Prompt effectiveness6. 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. (ref:hirist.tech)