Execute structured test plans across open source repositories, sample applications, SDK extensions, and AI workflow integrations.
Perform functional, integration, and regression testing on frameworks, applications, notebooks, scripts, APIs, and reference implementations.
Validate reproducibility of AI workflows in Jupyter and Google Colab environments.
Test agent-generated code outputs to ensure correctness, determinism, and alignment with expected B2 usage patterns.
Identify defects, edge cases, and environment inconsistencies; document findings clearly in Jira, GitHub, or other QA systems.
Coordinate retest cycles with Engineering and confirm resolution of reported issues.
Maintain baseline test scenarios aligned to common ICP workflows and real-world B2 storage use cases.
Support CI validation processes to ensure ongoing test coverage across releases and updates.

QA analyst or junior to mid-level QA engineer with strong technical understanding of AI workflows.
Experience executing functional and regression tests in Python-based environments.
Comfortable running notebooks, scripts, and example applications to validate expected behavior.
Strong attention to detail and ability to perform repeatable validation cycles efficiently.
Clear documentation and communication skills when reporting defects and edge cases.
Familiarity with cloud storage concepts and API-driven systems.
Exposure to AI workflows, agent-based systems, or data pipeline validation is preferred.

QA Engineer, Open Source AI

Key skills