QA Engineer, Open Source AI

About Backblaze

Backblaze provides reliable, high-availability cloud storage trusted by consumers, SMBs, enterprises, and developers in over 150 countries. Backblaze B2 Cloud Storage supports data-intensive workloads including backup, media, analytics, and modern AI pipelines. Our teams focus on building durable, scalable systems with a strong emphasis on developer experience, operational excellence, and product reliability.

But while there is a lot to celebrate in our past, there is almost as much opportunity ahead of us. We’re seeking a QA Engineer, Open Source AI to join our team!

About the Role:

We are seeking a QA Engineer to validate and ensure the reliability of open source AI integrations, frameworks, and example applications built on Backblaze B2 Cloud Storage. This is a hands-on role at the intersection of quality engineering and a fast-moving AI ecosystem, where the frameworks and applications you are testing are designed to support real AI workflows. This role is expected to actively use the latest AI coding agents and tools as part of everyday testing and validation work.

The primary objective is to execute structured testing across AI workflows, notebooks, frameworks, and integration examples to guarantee reproducibility, correctness, and production readiness. This includes validating end-to-end applications that demonstrate how B2 supports data ingestion, model storage, and retrieval across AI pipelines. This role requires continuous learning and ongoing evaluation of emerging AI frameworks and APIs as they evolve, and you will partner closely with Engineering and Product to ensure all public-facing assets meet high standards for stability, clarity, and usability.

What You’ll Do:

• 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.

Tools and Technologies:

• Python, Jupyter notebooks, Google Colab
• Backblaze B2 SDKs and REST APIs
• Jira, TestRail, GitHub Issues
• pytest or lightweight testing libraries
• GitHub Actions and CI pipelines
• API validation tools such as Postman
• Basic command-line workflows

The Right Fit:

• 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.

Why Backblaze: 

• Ensure the reliability of open source AI integrations used by developers globally.
• Work at the intersection of AI, data workflows, and cloud storage.
• Collaborate closely with Engineering, Product, and Developer Experience teams.
• Competitive compensation and benefits.
• Remote-first culture supporting work-life balance.

At this point, we hope you're feeling excited about the job de