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Quality Engineer

Wellspring Worldwide

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Wellspring’s software and services discover, protect, and launch innovations.

$12.0M total funding raised· Backed by MK Capital, Plymouth Growth, Resurgens Technology Partners
FULL TIMERemote · United States162 employeesPosted Sep 28
quality engineeringplaywrightjmetertypescriptjavascriptc#javapythongithub actionsci/cdtest automationperformance testingapi testingai-assisted developmentrisk-based testingcloud-based systems

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POSITION SUMMARY

We are hiring a Quality Engineer to help shape how quality is engineered in an AI-driven development environment.  Quality Engineers at Wellspring operate with a high degree of autonomy and technical ownership, with meaningful cross-team influence. This role is ideal for an engineer who wants to remain hands-on, technically deep, and influential in shaping modern, AI-driven quality practices.

What You'll Do

Automated Quality Engineering

  • Design, implement, and maintain automated test suites using Playwright
  • Develop and maintain performance and load tests using JMeter
  • Create reusable test utilities, data strategies, and scalable testing patterns
  • Build and curate the shared foundation that AI-assisted authoring depends on so generated tests come out consistent
  • Keep the suite healthy as authoring volume increases

AI-Driven Quality Practices

  • Use AI-assisted tools to generate, refine, and maintain test cases, and test data
  • Direct coding agents through the full authoring loop providing context and reviewing output
  • Review generated tests with a critical eye for the ways they fail quietly
  • Use AI to find coverage gaps and propose edge cases, then apply your own judgment about which ones carry real risk
  • Use AI-assisted triage as a first pass on failures, separating likely regressions from flakes
  • Apply self-healing and auto-repair tooling deliberately, with guardrails, recognizing that a test which silently repairs itself can mask a genuine product regression
  • Apply risk-based testing to focus effort on business-critical and defect-prone areas
  • Validate AI-enabled product behavior for correctness, reliability, and unintended outcomes
  • Feed recurring defect and failure patterns back into shared context and conventions so the same class of miss does not recur

CI/CD & Engineering Integration

  • Integrate automated tests into GitHub Actions–based CI/CD pipelines
  • Partner with Engineering and DevOps to improve pipeline quality gates
  • Manage test scope and execution sequencing to balance coverage, risk, and feedback time
  • Write tests and failure output that are legible to agents as well as engineers
  • Ensure quality gates hold as change volume increases, so higher delivery throughput does not quietly become higher-confidence mistakes

Quality Leadership & Collaboration

  • Collaborate with Product, Engineering, and Architecture to clarify requirements and identify quality risks early
  • Propose and drive solutions to technical and testing challenges with cross-functional partners
  • Help establish team standards for AI-driven test authoring
  • Document and communicate testing strategies, tradeoffs, and outcomes

What We're Looking For

Required Experience & Skills

  • Experience as a Quality Engineer, SDET, or Test Automation Engineer on production systems
  • Strong hands-on experience with Playwright (UI and API testing)
  • Experience with performance and load testing using JMeter or similar tools
  • Solid programming skills in TypeScript/JavaScript, C#, Java, or Python
  • Experience integrating automated tests into CI/CD pipelines, preferably GitHub Actions
  • Working knowledge of modern architectures, including web applications, APIs, and cloud-based systems
  • Demonstrated, sustained daily use of at least one modern AI-assisted development tool
  • Ability to critically review AI-generated tests and code — identifying shallow coverage, incorrect assumptions, and plausible-looking output that does not hold up

Ways You'll Stand Out

  • Experience testing AI-enabled or data-driven systems
  • Experience designing automation frameworks or shared testing infrastructure
  • Familiarity with observability, monitoring, or quality metrics beyond pass/fail testing
  • Experience building evaluation harnesses or test strategies for non-deterministic systems
  • Experience structuring context for AI tooling — prompt design, retrieval, or packaging codebase and domain knowledge for code and test generation
  • A point of view on where AI-assisted testing genuinely helps

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