About the job
Join Saily, where we revolutionize connectivity for travelers. Say goodbye to roaming fees and plastic SIM cards. We offer lightning-fast, secure mobile data in over 200 destinations worldwide. With millions of paying customers and countless travelers using Saily at any moment, our mission is to enhance the travel experience.
At Saily, we cultivate an AI-native Product Engineering culture that emphasizes:
- Engineers as builders responsible for end-to-end solutions, from concept to production.
- AI agents that empower engineers by automating repetitive tasks, allowing them to focus on impactful work.
- A collaborative environment where everyone is encouraged to suggest and implement improvements.
- A culture of curiosity, continuous learning, and knowledge sharing.
- Prioritizing customer satisfaction and ensuring a seamless journey for our users.
We believe in prioritizing growth over comfort, contribution over hierarchy, and impact over process. At Saily, we empower talented individuals with the context, autonomy, and AI tools necessary to excel in their roles.
Key Responsibilities:
- Design and implement robust test automation frameworks across multiple platforms, developing automated tests for complex functional integration, regression, and performance evaluations to ensure compliance with acceptance criteria.
- Contribute to the formulation and execution of testing strategies.
- Engage in the development of comprehensive test plans and test cases.
- Identify and document software defects, collaborating with the development team to resolve issues.
- Conduct hands-on exploratory and manual testing to identify edge cases and usability concerns that automated tests might overlook.
- Validate intricate user flows end-to-end across mobile and other platforms prior to major releases.
AI Integration & Advocacy:
- Proactively explore and incorporate AI-driven tools into QA workflows to enhance test creation, broaden coverage, and minimize cycle times.
- Promote the adoption of AI-assisted testing methodologies throughout the engineering organization.
- Experiment with large language models (LLMs) and AI assistants to generate test data, develop test cases from requirements, and manage flaky tests.

