Quality Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🔧 QA Engineer (Quality Assurance)

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Wellspring Worldwide

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

💰 Private Equity Round on 2022-07

Consulting • Healthcare • Logistics

Wellspring Worldwide is a company that powers world-class innovation management and technology commercialization programs. They serve leading corporations, universities, and government agencies by offering solutions in tech transfer, innovation management, tech scouting, and IP management. Wellspring provides tools and advice to manage R&D programs, technology portfolios, and corporate intellectual property. Their services include data and operations support, IP commercialization, and technology licensing. With 17 years in business, Wellspring is trusted by hundreds of organizations to handle millions of patents and trademarks and execute thousands of licenses online.

📋 Description

• 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 for consistent AI-generated tests • Keep the test suite healthy as authoring volume increases • Use AI-assisted tools to generate, refine, and maintain test cases and test data • Direct coding agents through the authoring loop by providing context and reviewing output • Review generated tests for silent failure modes • Use AI to find coverage gaps and propose edge cases, applying risk-based judgment • Use AI-assisted triage to distinguish likely regressions from flaky failures • Apply self-healing and auto-repair tooling with guardrails • Validate AI-enabled product behavior for correctness, reliability, and unintended outcomes • Feed recurring defect and failure patterns into shared context and conventions • 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 legible to both AI agents and engineers • Collaborate with Product, Engineering, and Architecture to clarify requirements and identify quality risks early • Drive solutions to technical and testing challenges with cross-functional partners • Establish team standards for AI-driven test authoring • Document and communicate testing strategies, tradeoffs, and outcomes

🎯 Requirements

• Experience as a Quality Engineer, SDET, or Test Automation Engineer on production systems • Strong hands-on experience with Playwright for 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 • Experience testing AI-enabled or data-driven systems is advantageous • Experience designing automation frameworks or shared testing infrastructure is advantageous • Familiarity with observability, monitoring, or quality metrics beyond pass/fail testing is advantageous • Experience building evaluation harnesses or test strategies for non-deterministic systems is advantageous • Experience structuring context for AI tooling, including prompt design, retrieval, or packaging codebase and domain knowledge for code and test generation, is advantageous • A point of view on where AI-assisted testing genuinely helps is advantageous