Architect and implement enterprise-grade QA frameworks covering functional, non-functional, performance, security, API, integration, data migration, AI/ML, mobile, accessibility, and IoT testing, aligned with industry standards and client-specific compliance requirements.
Lead large-scale, multi-vendor testing programs with full accountability for delivery, including scope, schedule, cost, risk, and quality, leveraging predictive analytics, KPI dashboards, and data-driven governance models.
Design and deploy AI/ML-driven test engineering solutions, including self-healing automation frameworks, intelligent test generation, and predictive defect analytics.
Drive the adoption of modern QA practices, including shift-left and shift-right testing, chaos engineering, model-based testing (MBT), service virtualization, and continuous testing within DevOps pipelines.
Integrate DevSecOps practices by embedding security testing (SAST, DAST, IAST), compliance validation, and container security into CI/CD workflows.
Lead cloud-native and microservices testing strategies, including validation of Kubernetes-based deployments, serverless architectures, and distributed systems with event-driven design.
Oversee performance engineering at scale, including workload modeling, capacity planning, and resilience testing for high-availability systems.
Establish test data engineering practices, including synthetic data generation, masking, and secure data provisioning aligned with regulatory frameworks such as GDPR and HIPAA.
Champion observability-driven testing by integrating monitoring tools (e.g., Prometheus, Grafana, ELK, OpenTelemetry) to enable real-time insights and proactive issue detection.
Define and enforce enterprise test governance frameworks, ensuring audit readiness, regulatory compliance (ISO 27001, SOC 2), and SLA adherence.
Lead automation framework engineering, enabling scalable, reusable, and parallelized test execution using tools such as Selenium Grid, Cypress, Playwright, and cloud-based testing platforms.
Collaborate with stakeholders, including C-suite executives, product owners, architects, and PMOs, to define quality benchmarks, manage risks, and communicate program health.
Manage and mentor globally distributed QA teams, driving capability development, workforce planning, and continuous upskilling across emerging technologies.
Oversee vendor partnerships, managed services, and outsourcing models, ensuring delivery excellence and continuous improvement.
Support pre-sales and solutioning activities by contributing to RFPs, technical proposals, and QA strategy design for new business opportunities.
Stay ahead of industry trends by evaluating and adopting emerging technologies such as autonomous testing agents, AI-assisted QA, and digital twin-based testing environments.
Requirements
7-9 years of progressive experience in software testing, quality engineering, and program delivery, preferably within fintech, telecom, healthcare, insurance, or enterprise IT domains.
Deep expertise in automation frameworks, API testing, performance engineering, security testing, and cloud-native QA practices.
Strong experience in microservices and distributed systems testing, including event-driven architectures and message queue validation (e.g., Kafka, RabbitMQ).
Proven track record of managing large-scale testing programs using Agile, Waterfall, and DevOps methodologies with measurable quality outcomes.
