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此界面为简体中文。雇主发布的职位名称和描述保留原文,可能为英文。

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Software Engineer Intern

ShopBack

远程工作

地点
Remote (United States)
工作安排
Intern
发布日期
2026年10月15日

申请前,请在雇主网站确认职位仍在招聘,并检查完整要求和条件。

职位描述

此界面为简体中文。雇主发布的职位名称和描述保留原文,可能为英文。

Our Journey The ShopBack Group is Asia-Pacific’s leading shopping, rewards, and payments platform, serving over 20 million active members across 13 markets. In 2025, the Group continued its global growth with its expansion into North America. Driven by the vision to make every day more rewarding, ShopBack is dedicated to saving members money and time, and delivering delight every day. The platform also enables merchants and brands to engage with their members in a cost-effective manner. Founded in 2014, ShopBack now powers over US$5.5 billion in annual sales for over 20,000 online and in-store partners, and has rewarded shoppers with more than US$900 million (over S$1 billion) in Cashback to date. Through its innovative offerings, ShopBack continues to create value for both members and merchants. Notably, its payment solution, ShopBack Pay, offers members a convenient and rewarding payment option at checkout. As a ShopBack intern, you do real work and deliver real impact. You ship code that goes to production and is used by millions of members all over the world. AI agents are part of how we build every day, so you will orchestrate and build with them from day one. What You'll Own Ship real features. You own a scoped project, from design to production, with a mentor who supports you. Build with AI as a teammate. You use coding agents to move fast, and you learn to review, test, and verify what they produce. Make AI tools for others. You build a skill, a tool, or an agent workflow that your team keeps using after your internship ends. Measure, don't guess. You write evals and tests so you can prove that your AI-powered work is good. Essentials to Succeed You have good fundamentals. You can write clean code, you are familiar with design patterns, and you understand data structures, APIs, and testing. You have built things outside of class. Side projects, hackathons, open source, and freelance work all count. You have applied AI, not only chatted with it. What have you built? Tell us about an app on an LLM API, a custom agent or MCP server, a boring task you automated end to end, or a simple eval you used to compare prompts or models. You stay curious and sceptical. You ask why the AI gave an answer, and you check it before you trust it. You learn fast. You are excited to learn new things. You are comfortable when you do not know something yet, and you ask good questions. Show Us What You Built with AI Tell us about: The coolest one: the thing you are most proud of, or the thing that made people say "wait, how?" Or the hardest one: the thing that broke many times before it worked. For each one, tell us: The problem: what you wanted to solve, and why it mattered to you. What you built: what you built, compared to what the AI did. What broke: where the AI failed, and how you found and fixed the problem. The result: a link to a repo, a demo, a video, or a write-up. A result that works with rough edges is better than slides that look polished. Start where the problem is real. A personal agent that saves your time 10 minutes every day is better than a big idea that nobody built. Build it, ship it, and let people use it. Bonus Points Agents: you built an agent that uses tools, keeps memory, or runs many steps without a human. Evals: you wrote evals or tests to measure whether your AI output improved. Real users: you shipped something that people other than you actually use. Cloud: you deployed your project to a cloud platform. We are looking for builders who are curious about AI and make a real impact with it. Technologies You'll Touch TypeScript / Node.js Postgres Kafka Kubernetes GitLab Datadog Claude Code MCP ShopBacker Traits Agency - We take ownership and act, rather than waiting for permission. When something's blocking progress, we find a way through it and follow through until it's done. Judgement - We aim for high-impact decisions, not just easy wins, and we put the bigger picture ahead of individual interests. That means moving quickly and confidently, while staying thoughtful about when a call really matters. Learning Velocity - We pick up new skills fast and let go of old habits just as quickly when something better comes along. We benchmark ourselves against the best and keep raising our own bar. Tenacity - We stay in it when things get hard, keeping a level head under pressure. We debate openly before deciding, then commit fully — and support each other along the way. What's in it for ShopBackers Career growth opportunities to take on greater challenges that help you realise your ambitions. Be part of a winning team on a journey to global scale. Competitive compensation based on performance. Candid, open, and collaborative culture where feedback is valued. Originally posted on Himalayas

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求职常见问题

为什么有些职位使用英文?

职位名称和描述由招聘企业撰写。为避免改变招聘要求或工作条件,我们保留原文。操作界面和本指南使用简体中文。如果中文搜索没有结果,可以尝试使用职位发布语言中的名称或技能,例如“software engineer”。搜索词不会自动翻译,界面语言也不代表企业要求的申请语言。

远程职位是否允许从任何国家工作?

不一定。企业可能对居住国家、工作许可或工作时段有要求。请查看原始招聘页面中的具体条件。如果未说明,应先向企业确认,再判断能否从你所在的地区工作。“远程”标签本身并不代表没有地点限制。

搜索没有结果时应该怎么办?

尝试更通用的职位名称或单个技能,并逐一移除筛选条件。不同企业可能用不同名称描述相似工作。如果某个职位已经消失,请在企业招聘页面搜索其职位编号。扩大搜索范围不会让已经关闭的职位重新开放。

申请会通过 ResumizeAI 直接提交吗?

申请按钮会打开外部网站。请按照企业或招聘服务的说明,在该网站完成并确认提交。在 ResumizeAI 中准备简历并不等于已经申请职位。如果链接只打开企业网站,请先找到对应职位,再继续申请流程。

如何针对职位调整简历和求职信?

将招聘要求与能够解释清楚的项目、任务和成果联系起来。突出相关经历,不要添加未经实际掌握的技能或虚构成绩。在求职信中用具体例子说明申请动机,并遵守企业要求的语言和文件格式。提交前检查两份文件,确保内容准确、联系方式正确、链接可用。