Live opening · Posted 9 days ago
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About Infinite:
Infinite is a global leader in digital engineering and IT services, with over 20 years of experience driving digital transformation. We partner with leading Fortune 1000 companies to deliver innovative, scalable technology solutions that accelerate business outcomes.
With deep expertise in telecommunications, healthcare, banking, and finance, Infinite helps organizations optimize and modernize their technology landscapes to achieve long-term growth and efficiency.
Experience:
18+ years of overall experience in Quality Assurance, Quality Engineering, Test Management, and Digital Transformation, with 10+ years leading large-scale QA Transformation initiatives across enterprise organizations.
Role Summary
We are seeking an experienced QA Transformation Leader to drive the strategic evolution of Quality Engineering across the organization. This leadership role will be responsible for transforming QA capabilities through a balanced focus on People, Process, and Technology.
The ideal candidate will establish a modern Quality Engineering ecosystem by building organizational capabilities, implementing QA Center of Excellence (CoE) standards, and accelerating adoption of Automation, AI/ML, and intelligent quality practices. This role requires strong executive presence, change management expertise, and the ability to influence stakeholders across business and technology organizations.
Key Responsibilities
1. People Transformation (Knowledge Management & Capability Building)
Define and execute the organization's Quality Engineering talent transformation strategy.
Develop competency frameworks, skill matrices, and career progression paths for QA professionals.
Establish enterprise-wide training, mentoring, and certification programs aligned with emerging testing technologies.
Build and maintain a centralized knowledge management framework, including best practices, reusable assets, playbooks, and learning repositories.
Drive workforce upskilling in Automation, AI-assisted testing, DevOps, Performance Engineering, and Quality Engineering practices.
Lead change management initiatives to transition teams from traditional testing to modern Quality Engineering approaches.
Create communities of practice and foster a culture of continuous learning and innovation.
Partner with HR, Learning & Development, and Technology leaders to identify and bridge skill gaps.
2. Process Transformation (QA Center of Excellence)
Establish and lead a scalable Quality Assurance/Quality Engineering Center of Excellence (QA CoE).
Define enterprise QA governance, standards, frameworks, policies, and operating models.
Design and implement standardized testing methodologies across Agile, DevOps, and Hybrid delivery models.
Develop quality metrics, KPI frameworks, dashboards, and reporting mechanisms for executive leadership.
Drive process maturity assessments and continuous improvement initiatives using industry best practices.
Define test strategy frameworks covering functional, integration, regression, API, performance, security, and UAT testing.
Standardize defect management, quality gates, risk assessment, and release readiness processes.
Ensure compliance with regulatory, audit, and organizational quality standards.
Promote shift-left and shift-right quality practices across development lifecycles.
3. Technology Transformation (AI/ML & Automation)
Define the enterprise roadmap for test automation, intelligent testing, and AI-driven quality engineering.
Lead adoption of AI/ML-enabled testing solutions including:
Test case generation
Test optimization
Predictive quality analytics
Defect prediction
Self-healing automation
Intelligent test execution
Drive automation strategy across UI, API, Mobile, Data, and Enterprise applications.
Evaluate and implement modern testing tools, frameworks, and platforms.
Establish reusable automation frameworks and enterprise-wide testing accelerators.
Collaborate with engineering and DevOps teams to integrate automated quality controls within CI/CD pipelines.
Leverage analytics and quality telemetry to improve release predictability and customer experience.
Drive innovation through GenAI, AI-assisted quality engineering, and emerging testing technologies.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
18+ years of experience in Quality Assurance, Quality Engineering, Test Management, or Software Quality leadership roles.
12+ years of proven QA transformation leadership experience overseeing enterprise-wide initiatives.
Experience establishing and leading QA CoE organizations supporting multiple portfolios and business units.
Strong experience driving organizational change and quality transformation programs.
Demonstrated success implementing enterprise test automation strategies.
Experience integrating Quality Engineering practices within Agile, DevOps, and CI/CD environments.
Strong understanding of AI/ML applications within testing and quality engineering.
Proven leadership experience managing large, geographically distributed teams.
Excellent stakeholder management and executive communication skills.
Preferred Qualifications
Experience leading Digital Transformation programs in large enterprise environments for atleast 10 years.
Knowledge of GenAI-powered testing solutions and modern quality engineering platforms.
Experience with cloud-native technologies (Azure, AWS, or GCP).
Familiarity with enterprise applications such as SAP, Salesforce, Oracle, and Microsoft platforms.
Certifications such as:
ISTQB Advanced/Test Manager
PMP or PgMP
SAFe Agilist
Lean Six Sigma
Certified Agile Leadership
Key Competencies
Leadership
Strategic Vision & Execution
Organizational Change Management
Executive Stakeholder Management
Talent Development & Coaching
Cross-functional Leadership
Process Excellence
QA CoE Establishment
Governance & Compliance
Quality Metrics & Reporting
Continuous Improvement
Delivery Excellence
Technology
Test Automation Strategy
AI/ML & GenAI Adoption
DevOps & CI/CD Integration
Quality Engineering Transformation
Test Data & Environment Management
Automation coverage and adoption improvements.
Reduction in production defects and escaped defects.
Improved release quality and deployment frequency.
Increased QA productivity through AI/ML and automation adoption.
Workforce certification and skill development targets achieved.
Standardized QA CoE processes implemented across portfolios.
Improved quality maturity scores and customer satisfaction metrics.
Work arrangement
No
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