Associate Director - QA (AI / ML)

GreyOrange is seeking an experienced and visionary associate director of quality assurance to lead enterprise-wide quality engineering initiatives across our AI-driven warehouse automation, fulfillment orchestration, and supply chain solutions. The ideal candidate will be responsible for defining quality strategy, driving engineering excellence through automation, adopting AI-powered testing innovations, and leading high-performing QA and SDET teams to ensure exceptional product quality across SaaS and packaged deployments.

The core responsibilities for the job include the following:

Quality Strategy and Governance:

• Define, implement, and continuously evolve the quality engineering strategy aligned with organizational goals, product roadmaps, and customer expectations.
• Own end-to-end quality governance across integration, system, end-to-end, performance, security, and user acceptance testing (UAT).
• Lead the adoption of Shift-Left quality practices and continuous testing across Agile and DevOps environments.
• Establish quality metrics, governance frameworks, and KPIs to improve release predictability, customer satisfaction, and reduce production defects.
• Drive quality ownership across engineering teams and foster a quality-first culture.
• Define and execute testing strategies at the Agile Release Train (ART) level, ensuring alignment with business objectives and product delivery commitments.

Automation and Engineering Excellence:

• Architect, implement, and scale robust automation frameworks across UI, API, microservices, and platform testing.
• Establish automation standards, reusable test assets, coding best practices, and quality gates integrated within CI/CD pipelines.
• Provide strong technical leadership with hands-on expertise in Python and modern test automation technologies.
• Drive automation-first engineering practices to maximize automation coverage and minimize manual testing effort.
• Lead the adoption of modern testing tools and frameworks, including Playwright, Selenium, PyTest, API automation frameworks, and cloud-based testing solutions.
• Continuously improve test execution efficiency, reliability, and maintainability through engineering best practices.

AI-Driven Quality Engineering and Innovation:

• Lead the transformation of quality engineering through AI-powered tools and practices.
• Drive adoption of AI solutions for automated test generation, intelligent test optimization, root cause analysis, self-healing automation, defect prediction and risk assessment, quality analytics, and productivity enhancement.
• Champion the effective use of modern AI platforms and developer productivity tools, including Cursor, Claude, GitHub Copilot, ChatGPT, and emerging quality engineering technologies.
• Evaluate and implement innovative testing approaches that improve speed, coverage, and quality outcomes.

People Leadership and Organizational Development:

• Build, mentor, and lead high-performing QA, automation, and SDET teams across multiple product lines.
• Manage managers, leads, and senior engineers while fostering a culture of ownership, collaboration, innovation, and continuous learning.
• Drive talent acquisition, succession planning, capability development, performance management, and career growth initiatives.
• Establish clear quality objectives and accountability frameworks across teams.
• Promote servant leadership principles while effectively managing stakeholder expectations and resolving organizational challenges.

Cross-Functional Collaboration and Stakeholder Management:

• Partner closely with Product Management, Engineering, Program Management, and Delivery teams to ensure quality objectives are achieved throughout the product lifecycle.
• Collaborate with business stakeholders to align quality strategies with customer requirements and operational goals.
• Provide executive-level reporting and insights on quality trends, risks, release readiness, and continuous improvement initiatives.
• Support both SaaS and customer-specific deployments with scalable quality processes and governance.

Domain Quality Leadership:

• Develop and execute quality strategies for Warehouse Management Systems (WMS), Inventory Management Solutions, Supply Chain Execution Platforms, Material Handling Automation Systems, Robotics, and Fulfillment Orchestration Solutions.
• Partner with product and domain experts to ensure comprehensive business process validation and end-to-end operational quality.
• Drive quality initiatives that support highly scalable, mission-critical warehouse and logistics operations.

Tools, Governance, and Metrics:

• Establish and manage quality dashboards, reporting frameworks, and engineering scorecards.
• Drive effective utilization of JIRA, test management tools, CI/CD platforms, and quality analytics solutions.
• Define release quality criteria, defect management processes, and governance mechanisms.
• Monitor and improve key engineering metrics including automation coverage, defect leakage, test execution effectiveness, release readiness, MTTR (mean time to resolution), production incident trends, and customer escaped defects.

Key Success Metrics:

• Reduction in production defect leakage.
• Increase in automation coverage and execution efficiency.
• Improved release predictability and overall product quality.
• Faster feedback cycles through Shift-Left and Continuous Testing practices.
• Successful adoption of AI-driven quality engineering solutions.
• Development and retention of high-performing QA engineering teams.

Requirements:

• Bachelor's or master's degree in computer science, software engineering, information technology, or a related field.
• 12-15 years of progressive experience in quality assurance, test automation, and quality engineering.
• Proven track record of leading large QA organizations and managing managers, leads, and distributed teams.
• Experience driving enterprise-scale quality engineering transformation initiatives.

Technical Expertise:

• Strong hands-on expertise in Python programming and automation framework architecture.
• Deep experience with Playwright, Selenium, PyTest, API testing and automation, microservices testing, performance testing, and CI/CD integration.
• Strong understanding of agile methodologies and DevOps practices, continuous testing, cloud-native architectures and distributed systems, and SaaS platforms.
• Hands-on exposure to AI-powered engineering and testing solutions.

Leadership and Soft Skills:

• Exceptional leadership, communication, and stakeholder management capabilities.
• Strong strategic thinking and execution skills.
• Ability to influence cross-functional teams and drive organizational change.
• Excellent problem-solving, decision-making, and conflict-resolution abilities.

Preferred Qualifications:

• Experience in warehouse management, supply chain, logistics, robotics, or material handling automation domains.
• Exposure to AI-driven fulfillment, inventory optimization, and warehouse orchestration platforms.
• Experience working in global product organizations delivering enterprise-scale software solutions.
• Knowledge of quality engineering practices for robotics-integrated platforms and real-time operational systems.