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We are looking for a forward-thinking Software Development Engineer in Test who views Artificial Intelligence as a partner in productivity. You are not just comfortable with code — you are skilled at leveraging AI to automate the mundane, solve complex debugging puzzles, and accelerate the delivery of life-saving software. In this role, you will play a critical part in ensuring software quality through advanced automation, AI-augmented testing practices, and close collaboration with cross-functional engineering teams.
Job Responsibility
Implement and maintain an end-to-end automation test framework for running UI integration tests and quality dashboards using Java, TypeScript, Cypress, Playwright, Cucumber, and JUnit
Leverage AI-assisted coding tools (e.g., GitHub Copilot, Cursor) to rapidly bootstrap test suites, refactor legacy test code, and generate comprehensive documentation
Implement automated API testing using tools such as REST Assured
Work closely with the development team to improve unit test coverage, frameworks, and productivity tools, utilizing LLMs to identify edge cases and boundary conditions that traditional manual analysis might miss
Participate in requirements, architecture, and design specification reviews
Perform peer code reviews, using AI to assist in identifying security vulnerabilities and architectural inconsistencies
Use defect management tools such as JIRA and XRAY
Manage source code with GIT and optimize CI/CD workflows using AI-driven insights for flaky test detection and build optimization
Develop and maintain GitHub Actions CI/CD pipelines
Develop load and performance tests using tools such as JMeter and K6
Follow a scaled agile software development process
Requirements
B.S. or M.S. in Computer Science or an equivalent field
3–5 years of experience in software development in test or software test engineering
Proven experience in Software Development in Test with proficiency in Behavior Driven Development (BDD)
Proficiency in Java, TypeScript, Cypress, Playwright, Cucumber, and JUnit
Demonstrated competency in AI-augmented development
ability to write effective prompts for code generation, debugging, and test data synthesis
Hands-on experience with AI productivity tools such as GitHub Copilot, OpenAI API integrations, or similar LLM-based suites
Experience in API and UI test automation
Experience using Agile software development tools and methodologies
Basic knowledge of microservice architecture, AWS services, Docker, CI/CD, Linux, and shell scripting
Nice to have
Experience in infrastructure and framework testing
Experience with testing bioinformatics software
Experience building or fine-tuning custom AI agents or scripts to automate repetitive QA manual tasks or log analysis
What we offer
An international community bringing together more than 110 different nationalities
An environment where trust is central: 70% of our leaders started their careers at the entry level
A strong training system with our internal Academy and more than 250 modules available
A dynamic work environment that frequently comes together for internal events (afterworks, team buildings, etc.)