QA Engineer

Rad AI applies deep learning to radiology in order to save lives and reduce the cost of healthcare. We believe that strong teams working closely together create audacious companies that transform our world for the better.

Our world-class team of engineers is building and deploying products that will make a difference in millions of people’s lives. You’ll be an early team member, helping us shape the long-term vision for Rad AI’s future.

Here at Rad AI, we’re focused on transparency, inclusion, close collaboration, and building an incredible team. Come and help us make a difference!

Here's what you'll do

• Work closely with the product team and developers to ensure clarity of feature requirements
• Develop deep expertise in our products and features and drive for product quality
• Champion and promote QA productivity through automation, tools, and other best practices
• Manage high volumes of QA testing and plan projects within a Windows Desktop environment
• Develop and maintain testing strategy, plans and test scripts for our services
• Prepare test cases, test data and environment based on requirements
• Execute tests manually or automatically, including in healthcare system environments
• Plan and conduct suitable vulnerability testing to verify system security
• Provide user-reported issue verification and participate in failure investigations
• Monitor and track software defects and establish quality metrics and best practices for QA process

This is what you'll need

• In-depth experience with Windows Desktop application testing in a healthcare environment
• BS degree or higher in Computer Science, Engineering, or a closely related field
• Strong understanding of software QA methodologies, tools, and approaches (black box and/or automated testing)
• Solid background in developing QA processes and metrics from the ground up
• Experience in setting up automated testing pipelines, collection and aggregation of application and test result metrics
• Hands on experience with automation tools and frameworks and a good familiarity with development and build tools
• Familiarity with Agile development process and tools (e.g. JIRA)
• Excellent follow-through and communication skills, including with non-technical team members and customers
• Self-motivated and very detail-oriented; takes pride in one’s work and strives for excellence

This would be nice to have

• Prior experience or interest in working and interfacing with machine learning and data science teams
• Working experience within a HIPAA or SOC 2 compliant environment
• Experience working within a hyper-growing early stage startup environment

Thank you for your interest. We look forward to hearing from you.

At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.