Senior Manager - Delivery Assurance

The Delivery Assurance Manager will drive high-quality, consistent, and predictable delivery across the organisation by combining strong Quality Assurance leadership with a structured Delivery Assurance framework. This role spans 70% Quality Assurance Leadership and 30% Delivery Assurance Framework and Governance. The role is expected to transform QA into a proactive, automation-first, and AI-assisted function, while building standardised delivery processes that ensure repeatability, compliance, predictability, and improved business outcomes.

The candidate will have responsibilities across the following functions:

Quality Assurance Leadership - 70%:

• Define and implement a comprehensive QA strategy aligned with organisational delivery goals.
• Embed automation-first and AI-enabled practices across QA.
• Standardise QA methodologies, processes, and quality benchmarks across delivery streams.
• Oversee the end-to-end QA lifecycle, including: Test planning, Test 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, Automated documentation.
• Evaluate and implement modern QA tools, including self-healing automation frameworks and AI-driven testing platforms.
• Build, mentor, and lead a high-performing QA team with a focus on automation and AI capability development.
• Strategise AI usage across all Quality Assurance-related processes.
• Drive Quality Assurance automation.
• Prepare Quality dashboards and publish 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.

Delivery Assurance Framework - 30%:

• Design and implement a scalable Delivery Assurance framework to ensure consistent and predictable outcomes.
• Establish standardised processes and governance mechanisms across delivery teams.
• Define and enforce compliance and quality standards across projects.
• Strategise and implement the use 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.
• Analyse delivery trends and drive continuous improvement initiatives.
• Ensure a quality mindset across teams.
• Work towards improving FCR and sustaining knowledge retention among teams.
• Continuously improve the factors that strengthen delivery assurance.

Requirements:

• Bachelor's/Master's degree in Computer Science or a related field.
• 12-15+ years of experience in IT delivery with strong QA leadership exposure.
• Experience in defining QA strategies and Delivery Assurance frameworks.
• Certifications such as ISTQB, PMP, Agile, or AI/ML Foundation are an advantage.

The candidate must meet the following requirements:

Quality Engineering and 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 and 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 and Execution:

• Strong analytical and problem-solving skills.
• Data-driven decision-making mindset.

Soft Skills:

• Ability to lead and motivate personnel.
• Strong organisational skills.
• Strong analytical skills.

Expected Success Metrics for the Role:

Quality and Delivery Outcomes:

• Reduction in defect leakage and rework.
• Improved first-time-right delivery quality.
• Increased delivery predictability and consistency.

Automation and AI Adoption:

• Increased automation and AI-led test coverage.
• Reduction in manual effort and QA cycle time.

Governance and Compliance:

• High adherence to quality, compliance, and governance standards.
• Reduction in audit gaps and risks.

Stakeholder and Customer Satisfaction:

• Strong collaboration and alignment with Delivery, PMO, and Business teams.
• Measurable improvement in CSAT/NPS across stakeholders.
• Positive shift in the perception of QA as a value-adding partner.