出海雷达

手动测试工程师

Manual QA Engineer

AI开发工程限定地区(需当地身份)日间重叠约 2 小时,需偶尔早起或晚睡
公司Globaldev Group
薪资未公开
工作地点Poland
地域资格限定地区(需当地身份)
时区要求日间重叠约 2 小时,需偶尔早起或晚睡
用工类型Full Time
发布时间13 天前
数据来源Himalayas
前往 Himalayas 查看并投递 →
注意地域限制:该职位明确限定在 Poland 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
作息提示:日间重叠约 2 小时,需偶尔早起或晚睡。

是一个由实时移动受众驱动的卖方全渠道广告平台。我们每天在全球数千个领先的应用程序和网站上投放数亿条广告。我们的平台利用人工智能,为数字广告活动提供更高效、有效和精准的解决方案。我们与数千个移动出版商直接集成,使我们每天能够获取全球超过500亿个第一方数据信号。营销人员使用这些匿名信号来了解和预测消费者行为,发现新机会并推动业务增长。

我们正在寻找一位具备实战经验的AI QA技术负责人,通过人工智能推动我们QA组织的技术发展。您的任务是在整个QA生命周期中识别机会,并将其转化为实用、可扩展的AI驱动能力,帮助整个QA团队更快、更智能、更高质量地工作。您将设计和构建由QA工程师在测试生命周期中使用的AI驱动工具、代理、工作流和集成——从测试设计和自动化到测试数据生成、调试和故障调查。这是一个注重实战的技术领导职位,重点在于构建、实验和创新。

要求

  • 5年以上软件质量工程、测试自动化或软件工程方面的实战经验
  • 熟悉测试自动化框架,如Playwright、Cypress或类似工具
  • 精通JavaScript/TypeScript或Python编程
  • 具备使用LLMs构建AI驱动工具、应用、工作流或代理的实战经验
  • 对代理工作流、提示和上下文工程、工具调用、MCP和API集成有实际理解
  • 有将实验性解决方案转化为可靠且可维护的工程产品的经验
  • 扎实的QA基础,包括测试设计、回归测试和探索性测试
  • 熟悉API、数据库和分布式系统
  • 熟悉CI/CD系统,如GitHub Actions、Jenkins或类似工具
  • 强大的问题解决能力,能够独立推动技术项目

加分项

  • 有评估LLM或代理输出并衡量AI解决方案质量的经验
  • 有构建内部开发者、工程或QA平台的经验
  • 有可观测性和分布式系统的经验
  • 有将AI与GitHub、Jira、Confluence或CI/CD平台等工具集成的经验
  • 有相关经验
查看英文原文

is a sell-side omnichannel advertising platform powered by real-time mobile audiences. We deliver hundreds of millions of ads per day across thousands of global leading apps and websites. Our platform uses AI to deliver more efficient, effective and precise digital advertising campaigns. Our direct integration with thousands of mobile publishers gives us access to more than 50 billion first-party data signals per day across the globe. Marketers use these anonymized signals to understand and predict consumer behavior, identify new opportunities and fuel business growth.
We are looking for a hands-on AI QA Technical Lead to drive the technical evolution of our QA organization through AI. Your mission will be to identify opportunities across the QA lifecycle and turn them into practical, scalable AI-powered capabilities that help the entire QA team work faster, smarter and with higher quality. You will design and build AI-powered tools, agents, workflows and integrations used by QA engineers across the testing lifecycle - from test design and automation to test data generation, debugging and failure investigation. This is a hands-on technical leadership role with a strong focus on building, experimentation and innovation.
Requirements

  • 5+ years of hands-on experience in Software Quality Engineering, Test Automation or Software Engineering.
  • Strong experience with test automation frameworks such as Playwright, Cypress or similar.
  • Strong programming skills in JavaScript/TypeScript or Python.
  • Hands-on experience building AI-powered tools, applications, workflows or agents using LLMs.
  • Practical understanding of agentic workflows, prompt and context engineering, tool calling, MCP and API integrations.
  • Experience turning experimental solutions into reliable and maintainable engineering products.
  • Strong QA fundamentals, including test design, regression testing and exploratory testing.
  • Experience with APIs, databases and distributed systems.
  • Experience with CI/CD systems such as GitHub Actions, Jenkins or similar.
  • Strong problem-solving skills and ability to independently drive technical initiatives.

Will be a plus

  • Experience evaluating LLM or agent output and measuring AI solution quality.
  • Experience building internal developer, engineering or QA platforms.
  • Experience with observability and distributed systems.
  • Experience integrating AI with tools such as GitHub, Jira, Confluence or CI/CD platforms.
  • Experience with Kubernetes or cloud infrastructure.
  • AdTech or programmatic advertising experience.

Responsibilities

  • Design, build and evolve AI-powered tools, agents and workflows that improve the efficiency and quality of the QA team.
  • Identify repetitive or high-impact QA activities and turn them into scalable AI-enabled solutions.
  • Build integrations between AI capabilities and our testing, engineering and internal systems.
  • Define technical standards and best practices for AI-powered QA solutions, including prompts, context, tools, agent workflows and human-in-the-loop processes.
  • Build mechanisms to evaluate AI output, measure quality and detect regressions.
  • Monitor and improve the reliability, performance and cost of AI-powered solutions.
  • Act as the technical focal point for AI within the QA team and help drive adoption, knowledge sharing and experimentation.
  • Work closely with QA engineers and engineering teams to turn real-world challenges into practical solutions.

What we offer

  • Dedicated help and support from our caring HR team.
  • 20 days of paid vacation.
  • Multisport membership coverage.
  • Comprehensive health insurance.
  • And, last but not least, competitive compensation that reflects your contribution and efforts.

Originally posted on Himalayas

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