Senior Manager

Company Brief :

Our end client is a globally recognized manufacturer of specialty architectural building products, operating across 30+ locations in 20 countries worldwide. The organization delivers innovative solutions such as interior wall and door protection systems, entrance flooring, expansion joint covers, louvers, grilles, sun control systems, specialty ventilation products, and privacy track/curtain solutions. Its customers include architects, designers, building owners, facility managers, and contractors across diverse sectors. Established in 1948 and headquartered in New Jersey, the company has a strong legacy of delivering high-quality, performance-driven, and sustainable building solutions that enhance functionality, safety, and design aesthetics.

Role & responsibilities

1. Quality Assurance Leadership (70%)

• Define and implement a comprehensive QA strategy aligned with organizational delivery goals, embedding automation-first and AI-enabled practices.

• Standardize QA methodologies, processes, and quality benchmarks across delivery streams.

• Oversee end-to-end QA lifecycle including test planning, execution, defect management, and reporting.

• Implement QA governance through periodic audits, reviews, and process adherence checks.

• Drive adoption of AI/GenAI-enabled QA practices, including test case generation, defect prediction, test optimization, and automated documentation.

• Evaluate and implement modern QA tools such as self-healing automation frameworks and AI driven testing platforms.

• Build, mentor, and lead a high-performing QA team with focus on automation and AI capability development.

• Strategize AI usage in all Quality Assurance related processes

• Drive automation Quality Assurance

• Preparing the Quality dashboards and publishing them to Senior Management

• Strengthen stakeholder collaboration across Delivery, PMO, Business, and Technology teams.

• Proactively identify risks and drive mitigation plans using data-driven insights.

• Track QA metrics and continuously improve quality and productivity.

2. Delivery Assurance Framework (30%)

• Design and implement a scalable Delivery Assurance framework to ensure consistent and predictable outcomes.

• Establish standardized processes and governance mechanisms across delivery teams. Define and enforce compliance and quality standards across projects.

• Strategize and implement the usage of AI to improve Delivery Processes

• Build delivery dashboards and KPIs to enable performance monitoring and decision-making.

• Introduce data-driven and predictive insights into delivery health tracking.

• Conduct governance reviews and audits to ensure adherence to frameworks.

• Analyze delivery trends and drive continuous improvement initiatives.

• Ensure a Quality mindset in the teams; work towards a better FCR and sustained Knowledge Retention among teams

• Continuously improve the factors that strengthen delivery assurance.

Key Skills & Competencies

Quality Engineering & QA:

• Strong experience in QA methodologies, test strategy, and automation practices.
• Experience transitioning from traditional QA to quality engineering practices.

AI Mindset in QA (Strong Exposure Preferred):

• Working knowledge of AI/ML concepts relevant to testing.

• Exposure to AI-enabled QA tools or GenAI use cases such as test case generation and analysis.

• Ability to identify practical AI use cases in QA and drive adoption.

• Strong inclination and capability to ramp up in AI-driven QA practices. Leadership & Collaboration:

• Proven ability to lead QA teams in complex delivery environments.

• Strong stakeholder management and influencing skills.

• Ability to drive cross-functional adoption of quality practices. Analytical & Execution:

• Strong analytical and problem-solving skills.

• Data-driven decision-making mindset.