AvasarAI

Quality Engineer

Wellspring Worldwide · 14 hours ago

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Not disclosed
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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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