Senior QA Automation Engineer - Greenfield Quality Architecture
Summary
Senior QA Automation Engineer architecting a greenfield quality platform for a healthcare benefits administration system, designing Playwright/TypeScript and PyTest automation across cloud services, data pipelines, and AI agent workloads.
At Nonstop Health, we are engineering the backbone of modern healthcare benefits administration - handling high-stakes financial replenishment, automated member card substantiation, and cutting-edge enterprise AI platforms. We are looking for a Senior QA Automation Engineer to lead a massive 0-to-1 technical initiative: designing and building our global quality control plane from the ground up.
This is not a role maintaining somebody else's test suite. You will have full technical autonomy to architect an enterprise-grade automation infrastructure, establishing automated quality gates across an estate of high-scale cloud services, complex data pipelines, and AI agent workloads.
The Engineering Challenge
- Build 0-to-1 Quality Infrastructure: Establish the foundational test automation strategy across our entire platform, transforming complex distributed environments into highly deterministic, automated pipelines.
- Tame High-Stakes Asynchronous Workflows: Healthcare benefits and financial payouts leave zero room for error. You will build test strategies that catch edge cases across multi-writer databases, background sync schedulers, and asynchronous payment loops before they reach production.
- Pioneer AI & Agentic Testing: Work at the bleeding edge of software quality by developing evaluation methods for multi-agent LLM architectures, isolated MicroVM execution substrates, and Model Context Protocol (MCP) tool integrations.
- Embed Continuous Verification: Partner directly with platform leads to seamlessly integrate end-to-end integration, API, and regression test suites into modern CI/CD delivery pipelines.
60 Days: Fast Ramp & Immediate Quick Wins
- Execute Estate Audit: Map critical manual workflows, zero-coverage endpoints, and high-risk silent failure points across primary customer portals and core payment/substantiation pipelines.
- Establish Core Framework: Spin up the initial Playwright (TypeScript) and PyTest (Python) test automation harness with standardized configuration and HIPAA-compliant test data handling.
- Deliver First Automated Gate: Ship automated smoke tests for the primary web portals (Member, Client, Channel) to immediately catch deployment regressions before release.
- Automate Pipeline Gating: Embed automated smoke and sanity regression suites directly into Bitbucket Pipelines, eliminating manual verification overhead for web deploys.
- Guard High-Risk Pathways: Build synthetic probes and automated checks targeting key backend APIs (REST/SOAP) and asynchronous state transitions to detect silent process failures automatically.
- Expand API Integration Testing: Automate verification for key transaction flows, verifying state updates across shared MongoDB collections and external counterparty boundaries.
90 Days: End-to-End Regression & AI Integration
- Full Core Coverage: Achieve comprehensive automated regression coverage across all core web applications, backend services, and batch jobs.
- AI & Agentic Quality Gates: Implement automated evaluation suites for Nonstop OS AI agent flows, validating tool call accuracy, MicroVM runtime state integrity, and audit log PHI/PII redaction.
- Contract & Resiliency Tests: Deploy automated contract checks against external counterparty web interfaces and APIs to catch upstream UI or data format changes before they break production flows.
6 Months: Total Automation & Scaled Autonomy
- Zero-Manual Deployments: Transition quality verification entirely to automated CI/CD gating, cutting deployment risk and manual testing effort to near zero.
- State Machine & Edge Case Verification: Establish robust testing for complex financial payout state machines, background schedulers, and recovery/resubmission logic.
- Quality Ownership: Serve as the technical quality lead- -establishing continuous testing patterns, maintaining test data isolation, and training engineering leads on writing maintainable integration tests.