质量工程师
Quality Engineer
关于Wellspring
Wellspring Worldwide, Inc. 是一家领先的基于网络的软件系统提供商，为大学、公司、政府机构和独立实验室提供研究、技术商业化和创新运营的管理解决方案。自2003年成立以来，Wellspring 已发展为全球超过500家组织提供服务，包括财富500强企业、中小企业、医院和大学。公司的旗舰产品——Evolve、Astria、Sophia 和 Flintbox——使组织能够管理整个创新生命周期，从发现和知识产权管理到商业化和知识转移。
职位概述
我们正在招聘一名质量工程师，帮助塑造在人工智能驱动开发环境中的质量工程方式。Wellspring 的质量工程师拥有高度的自主权和技术主导权，并对跨团队有实质性影响。这个职位适合一位希望保持动手能力、技术深度，并在塑造现代人工智能驱动的质量实践方面具有影响力的工程师。
你将负责的工作
自动化质量工程
- 使用 Playwright 设计、实现和维护自动化测试套件
- 使用 JMeter 开发和维护性能和负载测试
- 创建可重用的测试工具、数据策略和可扩展的测试模式
- 构建和维护 AI 辅助编写所依赖的共享基础，以确保生成的测试具有一致性
- 随着编写量的增加，保持测试套件的健康状态
人工智能驱动的质量实践
- 使用 AI 辅助工具生成、优化和维护测试用例和测试数据
- 通过完整的编写流程指导编码代理，提供上下文并审查输出
- 以批判性的视角审查生成的测试，关注它们如何静默失败
- 使用 AI 发现覆盖率缺口并提出边缘情况，然后根据自己的判断确定哪些情况具有真实风险
- 将 AI 辅助的优先级排序作为故障处理的第一步，区分可能的回归与偶然故障
- 有意识地应用自愈和自动修复工具，设置防护机制，认识到一个静默修复自身的测试可能会掩盖真正的产品回归
- 应用基于风险的测试，将精力集中在业务关键和易出错的领域
- 验证 AI 赋能的产品行为是否正确、可靠以及是否有意外结果
- 将重复出现的缺陷和故障模式反馈到共享上下文和规范中，防止同一类错误再次发生
CI/CD 与工程集成
- 集成自动化测试
查看英文原文
About Wellspring
Wellspring Worldwide, Inc. is a leading provider of web-based software systems for managing research, technology commercialization, and innovation operations for universities, companies, government agencies, and independent labs. Founded in 2003, Wellspring has grown to serve over 500 organizations globally, including Fortune 500 companies, SMEs, hospitals, and universities. The company’s flagship products—Evolve, Astria, Sophia & Flintbox—enable organizations to manage the entire innovation lifecycle, from discovery and IP management to commercialization and knowledge transfer.
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
Originally posted on Himalayas