Senior Automation Engineer

Senior Automation Engineer - SDET

About Josys

Josys is a modern AI-native identity security and governance platform. Enterprise AI adoption has made identity the fastest-growing attack surface, and the hardest to govern. Josys discovers, governs, and secures every identity — human, machine, and AI agent — across every application in the enterprise, allowing security and IT teams to surface risk, control access, and remediate identity threats in real-time. Trusted by over 1,000 organizations and MSPs worldwide, Josys turns identity from the fastest-growing attack surface into an autonomously governed advantage. For more information, visit josys.com .

About the role

The Josys QE function is undergoing a strategic transition toward an automation-first, data-driven, and AI-augmented model embedded in every engineering team. This role is essential to achieving our North Star of building a world-class QE function and transitioning to a full SDET-driven delivery model.

Technologies:

Cypress, Playwright/ Protractor, Pytest framework (Python),API testing, Database (SQL/ MySQL/ Postgres/ MongoDB), Performance tools (JMeter, K6), Test trail, Jenkins, TypeScript/JavaScript, Browser Stack, MERN Stack, Microservices, Containers/Orchestration, DevOps, HTML/CSS, JavaScript, Node.js, Express, React.js .

What You Will Do

Automation Framework: Implement, maintain, and extend the existing scalable automation frameworks for your dedicated engineering team.

Automation Development: Drive the "Automation First" goal by independently developing automation for complex, high-value features, ensuring coverage targets are met, and providing technical coaching to peers on advanced test development best practices.

Pipeline Execution: Implement and maintain automated quality gates (PR gate, release gate, post-deploy) within the CI/CD pipeline, ensuring adherence to governance standards.

Advanced Testing: Apply and implement advanced testing practices, including integration, end-to-end (E2E) automation, contract tests (e.g., Pact), performance tests, and service-level resiliency/chaos tests for your team's services.

Tooling Contribution: Contribute to the adoption and utilization of the standardized QE tooling strategy, focusing on high-quality automation and non-functional testing (NFT) execution.

Test Data Management: Execute and maintain the established test data management standards for compliant, on-demand, prod-like test data solutions, including PII masking and leveraging tools like Faker.js.

Shift-Left Support: Collaborate with developers, providing technical guidance to support the shift-left approach and improve the quality of unit and functional tests owned by the development team.

Required Qualifications

3+ years of experience in Cypress- Automation designing, implementing and supporting automated test solutions for SaaS products hosted on the cloud.

Expertise in implementing and enhancing automation frameworks for software teams.

Proven ability to implement automated tests for integration, E2E, and API/contract testing.

Experience with continuous integration tools and embedding automated quality checks into CI/CD pipelines.

Familiarity with defining and tracking key quality metrics (e.g., defect density, defect escape ratio, flaky rate).

Experience using test case management tools (e.g., TestRail) to manage test cases and trace them to JIRA stories.

Experience of Non-Functional Testing (NFT) concepts (e.g., performance testing, security testing) and the ability to execute existing test scripts.

Proven experience in leveraging AI/LLM tools (e.g., Cursor, ChatGPT) to accelerate QA workflows such as test generation, defect analysis, or synthetic test data creation.

Experience building internal bots, or developer-facing automation using AI

Experience to monitor automation suite health and assist in root cause analysis (RCA) for flaky tests.

Familiarity with emerging testing practices, such as knowledge of AI-augmented testing solutions.

Familiarity with Test Data Management (TDM) concepts and experience utilizing existing synthetic data generation tools.