Quality Assurance Manager
RSM US LLP (company site, opens in a new tab)10–12 yrsBengaluru, GurugramOn-siteDirect career pageEst. 18–30 LPA
Posted 22h ago
Reach people at RSM US LLP
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at RSM US LLP you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead and manage software quality assurance activities, including test strategy, automation, AI enablement, and defect management across multiple projects.
- Drive adoption of test automation, continuous testing, AI-assisted quality engineering, and responsible AI practices to improve software quality and team productivity.
- Mentor and develop QA teams, establish testing best practices, and provide technical direction for automation frameworks and quality standards.
Minimum Requirements
- Bachelor's degree in computer science, IT, engineering, or related field.
- 10-12 years of experience in software quality assurance, testing, or quality engineering with leadership responsibilities.
- Experience in testing activities supporting Workday implementations or enhancements (HCM, Financials, Payroll, Benefits, or integrations).
- Working knowledge of Playwright and Selenium for automation, generative AI tools for testing, API testing tools like Postman, and CI/CD tools such as Azure DevOps.
Ideal Candidate Profile
- Experienced leader in QA with background in large-scale enterprise applications and Workday-related projects.
- Strong hands-on and strategic expertise in test automation frameworks, AI-assisted testing, and quality metrics to support risk-based decisions.
- Able to guide teams in responsible AI adoption with a focus on governance, data protection, and measurable quality improvements within Agile environments.