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Medeloop

Software Quality Assurance (QA) Engineer

Medeloop, San Francisco, California, United States, 94199

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About Medeloop

Medeloop is creating the future of clinical operations and health research through cutting-edge AI and big data technologies. Our unified platform, spanning AI-powered analytics, study management, and grant automation, streamlines the entire research lifecycle, enabling faster, smarter, and more impactful discoveries across medicine and public health.

Recognized by Politico as the “AI Disrupter-in-Chief” for healthcare and public health, Medeloop is trusted by premier institutions across government, academia, and life sciences. Our platform leverages one of the largest and most diverse health data ecosystems in the industry, supporting AI researchers to drive breakthroughs in health equity, drug development, chronic disease, and more. Interested candidates can review a demo of one of our AI scientist research pipelines and read about our mission on our LinkedIn.

We are a fast-growing company backed by world-class investors and led by teams with expertise in AI, life sciences, and medical research. We are building tools to accelerate research timelines, expand access to insights, and save lives. Join us as we build the future of science.

Who You Are A driven QA Software Production Engineer who thrives in fast-paced environments and is excited to shape the future of quality engineering at a quickly ramping Medeloop. You will ensure the quality, reliability, and efficiency of our software releases across web platforms through rigorous end-to-end testing in both pre- and post-production phases of our web platform. Most importantly, you want to make a difference in the world!

Your Primary Focus Will Include

Designing, executing, and maintaining comprehensive testing strategies, including automated regression testing, smoke testing, and performance validation, to guarantee the reliability and stability of every release.

Drive test-driven development and play a key role in managing versioning, release cycles, and integrating with CI/CD pipelines to automate testing.

Set the standards and practices of other development engineers to ensure their software deliveries align with QA best practices.

Contribute to the development of scalable testing infrastructure that powers our platform’s capabilities.

Your Primary Responsibilities Will Include

Collaborate with engineering and product teams to define testable acceptance criteria and understand feature requirements and user flows.

Design, execute, and maintain test plans, including exploratory, regression, and smoke testing across our web platforms.

Develop and maintain automated test cases using industry-standard tools like Cypress, Playwright, or similar frameworks.

Identify, document, and prioritize bugs and quality issues, working cross-functionally to resolve them efficiently.

Oversee release and version control processes, including branching strategies and CI/CD pipeline integration.

Monitor production environments using observability tools such as Datadog and Sentry to ensure system health post deployment and continual improvement.

Track and report quality metrics to ensure release readiness.

Promote standard production engineering practices throughout the development lifecycle.

Qualifications The ideal candidate will have the following experiences:

4+ years of experience in QA, software production engineering, or related quality assurance roles.

Experience with both automated and manual testing methodologies, including unit, integration, end-to-end (E2E), regression, and smoke testing.

Proficiency with testing frameworks such as Jest, React Testing Library, Supertest, and pytest.

Hands-on experience with testing tools like Cypress, Playwright, Supertest, and pytest (including requests or Selenium-based testing).

Experience testing RESTful APIs using tools like Postman or Supertest.

Strong understanding of analytics pipelines and basic statistical methods.

Confidence working within a modern AWS-based infrastructure, including services like EC2, ECS, EMR, DynamoDB, and Aurora.

Experience validating data-intensive applications deployed across customer-managed cloud environments, including pipelines that run in AWS or hybrid setups when the customer uses a different cloud environment, and ensuring quality across varied infrastructure.

A desire to take on a leadership role in shaping how software is built, tested, and released.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

Industries

Data Infrastructure and Analytics

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