{"id":69619,"url":"https://alion.io/job/greyorange-associate-director-qa-ai-ml","title":"Associate Director - QA (AI / ML)","company":{"id":176318,"name":"GreyOrange","domain":"greyorange.com","url":"https://alion.io/company/greyorange-2","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":53000,"max_usd":129000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":49},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"ChatGPT","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"GitHub","optional":false},{"name":"Java","optional":false},{"name":"JMeter","optional":false},{"name":"Playwright","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Selenium","optional":false},{"name":"Self-Healing","optional":false},{"name":"Shift-Left","optional":false},{"name":"Shift-Left Security","optional":false}],"status":"live","first_seen_at":"2026-08-22T00:48:05Z","employer_posted_date":null,"last_verified_at":"2026-08-22T00:48:05Z","board_verified":false,"closed_at":null,"days_open":59,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":59},"description":"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.\nThe core responsibilities for the job include the following:\nQuality Strategy and Governance:\nDefine, implement, and continuously evolve the quality engineering strategy aligned with organizational goals, product roadmaps, and customer expectations.\nOwn end-to-end quality governance across integration, system, end-to-end, performance, security, and user acceptance testing (UAT).\nLead the adoption of Shift-Left quality practices and continuous testing across Agile and DevOps environments.\nEstablish quality metrics, governance frameworks, and KPIs to improve release predictability, customer satisfaction, and reduce production defects.\nDrive quality ownership across engineering teams and foster a quality-first culture.\nDefine and execute testing strategies at the Agile Release Train (ART) level, ensuring alignment with business objectives and product delivery commitments.\nAutomation and Engineering Excellence:\nArchitect, implement, and scale robust automation frameworks across UI, API, microservices, and platform testing.\nEstablish automation standards, reusable test assets, coding best practices, and quality gates integrated within CI/CD pipelines.\nProvide strong technical leadership with hands-on expertise in Python and modern test automation technologies.\nDrive automation-first engineering practices to maximize automation coverage and minimize manual testing effort.\nLead the adoption of modern testing tools and frameworks, including Playwright, Selenium, PyTest, API automation frameworks, and cloud-based testing solutions.\nContinuously improve test execution efficiency, reliability, and maintainability through engineering best practices.\nAI-Driven Quality Engineering and Innovation:\nLead the transformation of quality engineering through AI-powered tools and practices.\nDrive 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.\nChampion the effective use of modern AI platforms and developer productivity tools, including Cursor, Claude, GitHub Copilot, ChatGPT, and emerging quality engineering technologies.\nEvaluate and implement innovative testing approaches that improve speed, coverage, and quality outcomes.\nPeople Leadership and Organizational Development:\nBuild, mentor, and lead high-performing QA, automation, and SDET teams across multiple product lines.\nManage managers, leads, and senior engineers while fostering a culture of ownership, collaboration, innovation, and continuous learning.\nDrive talent acquisition, succession planning, capability development, performance management, and career growth initiatives.\nEstablish clear quality objectives and accountability frameworks across teams.\nPromote servant leadership principles while effectively managing stakeholder expectations and resolving organizational challenges.\nCross-Functional Collaboration and Stakeholder Management:\nPartner closely with Product Management, Engineering, Program Management, and Delivery teams to ensure quality objectives are achieved throughout the product lifecycle.\nCollaborate with business stakeholders to align quality strategies with customer requirements and operational goals.\nProvide executive-level reporting and insights on quality trends, risks, release readiness, and continuous improvement initiatives.\nSupport both SaaS and customer-specific deployments with scalable quality processes and governance.\nDomain Quality Leadership:\nDevelop 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.\nPartner with product and domain experts to ensure comprehensive business process validation and end-to-end operational quality.\nDrive quality initiatives that support highly scalable, mission-critical warehouse and logistics operations.\nTools, Governance, and Metrics:\nEstablish and manage quality dashboards, reporting frameworks, and engineering scorecards.\nDrive effective utilization of JIRA, test management tools, CI/CD platforms, and quality analytics solutions.\nDefine release quality criteria, defect management processes, and governance mechanisms.\nMonitor 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.\nKey Success Metrics:\nReduction in production defect leakage.\nIncrease in automation coverage and execution efficiency.\nImproved release predictability and overall product quality.\nFaster feedback cycles through Shift-Left and Continuous Testing practices.\nSuccessful adoption of AI-driven quality engineering solutions.\nDevelopment and retention of high-performing QA engineering teams.\nRequirements:\nBachelor's or master's degree in computer science, software engineering, information technology, or a related field.\n12-15 years of progressive experience in quality assurance, test automation, and quality engineering.\nProven track record of leading large QA organizations and managing managers, leads, and distributed teams.\nExperience driving enterprise-scale quality engineering transformation initiatives.\nTechnical Expertise:\nStrong hands-on expertise in Python programming and automation framework architecture.\nDeep experience with Playwright, Selenium, PyTest, API testing and automation, microservices testing, performance testing, and CI/CD integration.\nStrong understanding of agile methodologies and DevOps practices, continuous testing, cloud-native architectures and distributed systems, and SaaS platforms.\nHands-on exposure to AI-powered engineering and testing solutions.\nLeadership and Soft Skills:\nExceptional leadership, communication, and stakeholder management capabilities.\nStrong strategic thinking and execution skills.\nAbility to influence cross-functional teams and drive organizational change.\nExcellent problem-solving, decision-making, and conflict-resolution abilities.\nPreferred Qualifications:\nExperience in warehouse management, supply chain, logistics, robotics, or material handling automation domains.\nExposure to AI-driven fulfillment, inventory optimization, and warehouse orchestration platforms.\nExperience working in global product organizations delivering enterprise-scale software solutions.\nKnowledge of quality engineering practices for robotics-integrated platforms and real-time operational 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