About Acronis
Acronis provides integrated cybersecurity, data protection, and endpoint management solutions for managed service providers, small and medium businesses, enterprise IT departments, and home users. Its solutions help identify, prevent, detect, respond to, remediate, and recover from cyberthreats, supporting data integrity and business continuity.
Responsibilities
•Develop and maintain a unified quality strategy aligned with organizational and product goals
•Define QA standards, processes, tools, and governance mechanisms across product lines
•Lead quality improvement initiatives, audits, and transformation programs
•Drive the adoption of AI/ML-based quality, testing, and risk assessment tools
•Champion innovation, experimentation, and continuous improvement
•Define, track, and report quality metrics, including defect rates, release stability, automation effectiveness, and customer-reported issues
•Prepare executive-level quality reports and dashboards for C-level leadership
•Provide dotted-line leadership to approximately 150 QA/AQA professionals across 10 distributed product teams
•Mentor QA managers, leads, and senior engineers, fostering talent development and capability growth
•Build and maintain a competency framework covering automation, quality engineering, AI literacy, and modern testing disciplines
•Promote collaboration, consistency, and best-practice adoption across distributed teams
•Foster an efficiency-first mindset and commitment to quality, innovation, and customer value
•Oversee functional, regression, integration, performance, security, and automated testing practices
•Advance automation strategies and frameworks for CI/CD pipelines and modern engineering delivery models
•Support risk-based test planning and strategic testing for complex, multi-product environments
•Lead the integration of AI-assisted testing, generative AI tools, intelligent automation, and predictive quality insights
•Introduce tools and technologies that improve test effectiveness, coverage, and speed
•Ensure continuous learning and adaptation to emerging QA technologies, tools, and industry trends
•Align release criteria, quality gates, and readiness standards across product teams
•Partner with Engineering and Product to improve release stability, predictability, and performance
•Oversee defect detection and provide visibility into quality risks throughout the SDLC
•Participate in critical release reviews, escalations, and post-release evaluations
•Use AI tools and analytics to improve release risk assessment and decision-making
•Communicate risks, priorities, and release readiness to senior leadership in a timely manner
•Work with Product Management to ensure requirements are testable and quality expectations are defined
•Collaborate with Customer Support and Customer Success to resolve customer-found issues efficiently and sustainably
•Partner with Sales, Pre-Sales, and Services during escalations or customer-critical engagements
•Communicate quality risks, priorities, and metrics to stakeholders and executive leadership
•Identify cross-functional opportunities for automation, AI-enabled improvements, and operational efficiency
•Strengthen customer retention and competitive positioning through improved product quality and reliability
Requirements
•Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
•10+ years of QA, Quality Engineering, or Software Testing experience
•7+ years in QA leadership roles with responsibility across multiple products and global teams
•Experience with automation frameworks, CI/CD pipelines, and modern SDLC practices
•Proven ability to lead in a matrixed/dotted-line environment
•Experience with AI-assisted testing or ML-driven quality tools
•Strong communication and collaboration skills across technical and business functions
•Passion for quality, innovation, efficiency, and continuous improvement
•Experience preparing and presenting reports and insights to C-level executives
Nice to have
•Experience in SaaS, cloud platforms, or enterprise software
•Knowledge of generative AI, predictive analytics, or intelligent automation technologies
•Experience in large-scale QA modernization and organizational change initiatives
Conditions
No conditions specified in the posting.
