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Job Description
Structured overview of role & requirementsAbout This Role
Lead and execute enterprise-wide Quality Engineering strategy integrating AI-driven testing, automation, cloud-native, and performance engineering to enhance product quality and delivery speed.
Oversee development and scaling of AI-powered QA solutions including test automation, predictive analytics, and autonomous testing across multiple platforms and tool integrations.
Collaborate with cross-functional teams (Product, Engineering, DevOps, SRE) to ensure regulatory compliance, operational resilience, and improved customer experience through continuous testing and quality governance.
Minimum Requirements
15+ years in Software Testing, Quality Engineering, Automation or related domains with proven management experience in QA/QE teams and enterprise quality transformations.
Strong technical expertise with programming skills in Java, Python, JavaScript/TypeScript and experience with automation tools like Playwright, Selenium, and performance tools (JMeter, K6).
Experience with cloud platforms and DevOps tools: AWS services, Jenkins, Git pipelines, Docker, Kubernetes, and observability platforms like Datadog, Grafana.
Work Experience Required: 15+ years in relevant fields; Notice Period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced leader skilled at integrating AI/GenAI technologies into Quality Engineering for automation and predictive quality analytics.
Proven track record of driving enterprise-level QA transformation programs including cloud-native and microservices testing strategies.
Strong collaboration and influence capability across diverse teams (Product, DevOps, SRE) in regulated environments with measurable impact on automation coverage, defect reduction, and release confidence.
