• Design and execute comprehensive performance test strategies — Load, Stress, Soak, Spike, Scalability, and Endurance testing. • Develop and maintain performance scripts using tools such as JMeter, Gatling, LoadRunner, Locust, or k6. • Simulate realistic user traffic and workload models for distributed systems. • Perform root cause analysis across application, API, database, and infrastructure layers. • Define and maintain performance baselines, SLAs, and SLOs. • Integrate performance tests into CI/CD pipelines for continuous validation. • Build AI-driven performance analysis frameworks using pattern recognition and anomaly detection. • Develop custom test agents/orchestrators using MCPs to simulate large-scale, multi-node workloads. • Implement self-healing test systems that adapt dynamically to environment changes. • Use ML models to predict performance degradation and proactively optimize systems. • Automate root cause detection with AI-assisted observability insights. • Use observability tools (Grafana, Prometheus, Datadog, New Relic, AppDynamics) to monitor and analyze performance metrics. • Create visual dashboards to communicate trends and optimization opportunities. • Collaborate with SRE and development teams for end-to-end performance tuning. • Partner with engineering, QA, and platform teams early in the SDLC to define performance goals. • Conduct post-release reviews and contribute to testing standards and best practices.

• Review business requirements, technical specifications and design documents to provide timely and meaningful feedback • Create detailed, comprehensive and well-structured test plans and test cases • Identify, record, document thoroughly and track bugs • Perform thorough regression testing when bugs are resolved • Execute test cases both manually and automated and analyze results • Work with cross-functional teams to ensure quality throughout the software development lifecycle • Liaise with internal teams (e.g. development teams and product owners) to identify system requirements • Track quality assurance metrics, like defect densities and open defect counts • Stay up-to-date with new testing tools and test strategies • Monitor debugging process results • Great team player

• Own quality for core cybersecurity features and systems • Work side-by-side with security and platform engineers throughout the development lifecycle • Design test strategies for security-critical and adversarial scenarios • Build and maintain automated test frameworks and tooling (primarily Python) • Perform white-box testing and participate in design and code reviews • Test system-level properties: performance, reliability, scalability, failure modes • Debug complex issues, perform root cause analysis, and improve test coverage • Contribute to CI/CD pipelines and quality gates for security-sensitive releases

• Perform manual functional testing across new features and existing functionality • Design, write, review, and maintain clear and comprehensive test cases • Execute regression testing to ensure system stability after updates and releases • Conduct UI/UX testing, ensuring usability, consistency, and user experience standards are met • Validate integrations and workflows involving APIs, API keys, and related development tools • Test applications that interact with or leverage LLMs, demonstrating an understanding of how these systems work and respond • Identify, document, and track defects with high-quality bug reports • Review, validate, and manage bug creation and test outputs from offshore QA teams • Collaborate closely with product, engineering, and QA stakeholders to ensure high-quality releases • Act as a senior QA presence, providing guidance through best practices rather than direct supervision