As Engineering Leader, I spearheaded the shift-left QA strategy, embedding automation early in the SDLC.
He established unified backend and frontend frameworks using Playwright and Pytest, aligning them with GitLab CI for automated execution on code merges.

I also pioneered the use of AI-assisted test design, where tools like Copilot and GPT-based models generated test scenarios directly from acceptance criteria.
This reduced planning overhead and improved coverage consistency across teams.

I mentored QA engineers in implementing these AI workflows, fostering a culture of autonomous testing and faster feedback loops.

Key Achievements:

Reduced manual test design effort by 40% via AI-assisted generation.
Standardized automation frameworks across product teams.
Accelerated deployment confidence through early validation pipelines.

At SIXT, I architected a cloud-native test automation ecosystem that unified mobile, API, and performance testing within CI/CD.
He developed an Appium-based mobile automation suite integrated with Jenkins pipelines for parallel execution on Android and iOS, significantly reducing feedback cycles.

Sandal built a Spring Boot microservice that interfaced with Kubernetes to dynamically spin up and destroy test environments on demand — integrating Jacoco for real-time coverage analysis.

Performance and security validation were automated using Gatling, Lighthouse, and OWASP ZAP, embedding them directly into deployment pipelines to enforce quality gates.

Key Achievements:
Cut regression execution time by 50% through parallel and containerized testing.
Enforced DevSecOps practices by integrating security scans into build pipelines.
Created a coverage-driven release readiness dashboard for continuous quality visibility.

Led the design and development of an AI-powered test automation framework that transformed how front-end and API testing was executed. The framework integrated Playwright (TypeScript) for web UI testing and Pytest (Python) for GraphQL API validation, ensuring seamless coverage across layers.

Using Cline and GitHub Copilot, the system generated intelligent test scripts automatically from user stories and API specifications, significantly cutting down authoring time.
To enhance observability, Sandal implemented Grafana-Prometheus alerting to monitor test stability and detect regression trends in CI pipelines.

Additionally, the framework incorporated visual anomaly detection using AI models to verify React-based dashboards — ensuring that graphical widgets and performance metrics remained consistent after each release.
This initiative resulted in a 35% reduction in manual QA effort and established a reusable model for other teams.

Key Achievements:
Built a fully autonomous Playwright framework with modular plugin support.
Introduced AI-based visual validation, improving UI accuracy.
Integrated coverage-based prioritization to target high-value test cases.
Enhanced system reliability via Kafka, AWS, and Airflow fault testing.