heartflowinc
Senior Test Engineer
At a Glance
- Location
- San Francisco, California, United States
- Experience
- 5–8 years
- Compensation
- salary compensation range is $165,000 to $205,000, bonus, and equity. #LI-IB1 He
- Posted
- 2026-07-09T17:38:16-04:00
Key Requirements
Required Skills
Domain Knowledge
- Automation
- Engineering
- Medical
Requirements
5–8 years of experience in software test engineering, SDET, or quality engineering roles, with a strong hands-on automation background.
Required: Direct experience testing Software as a Medical Device (SaMD) or other regulated medical device software.
Required: Working knowledge of medical device QMS practices and applicable standards (e.g., ISO 13485, IEC 62304, ISO 14971, 21 CFR Part 820), including test documentation, traceability, and tool validation.
Demonstrated experience designing and maintaining E2E automation frameworks that cover complete workflows and system integrations.
Experience authoring test plans, protocols, and reports in a regulated environment, with attention to traceability between requirements, test cases, and evidence.
Practical experience with AI-assisted testing tools and techniques (e.g., AI-augmented test authoring, self-healing automation, LLM-driven test generation or triage).
Responsibilities
Design, implement, and maintain end-to-end (E2E) automated test suites that exercise complete user workflows across UI, API, and back-end services, executing against the architecture and standards set by the Test Architect.
Champion an AI-first automation strategy.
Implement and scale test coverage using AI-assisted authoring and generative test planning derived from AI-generated requirements, while leveraging intelligent triage to minimize maintenance overhead.
Build and own a baseline suite of daily smoke/build-acceptance tests covering core workflows across development and staging environments, closing a current gap where automated testing only runs during formal V&V cycles.
Lead post-deployment testing activities, including production smoke tests, monitoring-driven verification, and continuous validation against live environments.
Design and implement golden-dataset regression tests for HeartFlow's ML pipeline services, validating algorithmic outputs against curated reference cases.