Quality & Reliability Engineer (AI Systems & Workflow Assurance)

Clinically AI•San Diego, CA

1d•Hybrid

About The Position

Clinically AI is a healthcare AI company transforming how clinicians, administrators, compliance teams, and healthcare organizations manage documentation, chart auditing, and operational workflows through artificial intelligence. We are seeking a Quality & Reliability Engineer to ensure the stability, correctness, and performance of AI-native healthcare workflows and operational systems across the Clinically AI platform. This is not a traditional QA role focused only on manual testing or end-of-cycle validation. This role sits at the intersection of software reliability, workflow systems testing, AI behavior validation, and operational quality engineering in complex healthcare environments. You will ensure that clinicians, administrators, compliance teams, and operational users can confidently rely on AI-powered systems in real-world healthcare workflows. This includes validating system correctness, identifying edge cases in workflow behavior, improving release confidence, and ensuring that AI-driven outputs behave reliably within operational constraints. The ideal candidate thinks deeply about systems, workflows, edge cases, failure modes, and operational behavior, not just test cases. You should be excited by ensuring reliability in AI-native systems where outputs may be probabilistic, workflows are complex, and correctness directly impacts clinical operations. This role will work closely with product, engineering, implementation, and leadership teams in a highly collaborative and fast-moving startup environment.

Requirements

3+ years of experience in QA engineering, software testing, or reliability engineering roles in SaaS, web applications, or platform environments
Experience building automated test suites using Playwright or similar frameworks (Cypress, Selenium, WebdriverIO, etc.)
Strong understanding of frontend behavior, browser debugging tools, and network inspection
Experience validating REST APIs, including authentication, permissions, and data integrity
Proficiency in JavaScript or TypeScript for test automation
Experience working within CI/CD pipelines (GitHub Actions preferred)
Strong ability to identify root causes and communicate technical findings clearly
Experience collaborating closely with engineering and product teams in agile environments
High ownership mindset and ability to operate in fast-paced, evolving systems

Nice To Haves

Experience testing React applications, browser extensions, or real-time web systems
Exposure to mobile testing environments (iOS/Android)
Experience with performance or load testing tools (k6, JMeter, Locust)
Familiarity with cloud infrastructure and distributed systems
Experience working in regulated environments (HIPAA, SOC2, NIST)
Experience testing AI/LLM-powered or non-deterministic systems

Responsibilities

Ensure the stability, correctness, and performance of AI-native healthcare workflows and operational systems.
Validate system correctness in real-world healthcare workflows.
Identify edge cases in workflow behavior.
Improve release confidence.
Ensure AI-driven outputs behave reliably within operational constraints.
Collaborate closely with product, engineering, implementation, and leadership teams.