寻找你的下一个职业机会

按职位、技能和地点搜索招聘信息。准备申请前,先仔细了解职位要求。

找到一个吸引人的职位名称只是求职的起点。请将工作职责、招聘要求和工作条件与你的实际经历进行比较。本指南帮助你筛选机会、准备有针对性的申请材料,并确认每份申请应该在哪里提交。

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。

清除筛选

搜索结果: 12,766

← 返回搜索结果

Senior Full Stack Engineer

MWDN

远程工作

地点
Remote (Hungary)
工作安排
Full Time
发布日期
2026年10月11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。

Description MWDN is a global IT outstaffing company with 23+ years of experience that connects exceptional tech talent with leading companies across Israel, the USA, Great Britain, and Western Europe. We offer opportunities to work on international products in a stable and professional environment. Why does MWDN rock? Here’s what you can expect when you join MWDN: Security: We carefully vet our clients to minimize risks and ensure reliability and timely payments - no fraud or unpleasant surprises. Career support: If a project isn’t the right fit, we support you and actively help find new opportunities that match your skills and career goals. Legal assistance: We provide guidance on legal matters, including opening and managing your independent contractor or sole proprietorship status, taxes, and related processes. Professional development: We offer English courses and professional growth opportunities, as well as team-building events. Why choose us? MWDN is ranked among the top 5 IT employers in our region according to DOU. We take pride in our transparency and strong commitment to our team. Curious to learn more? See what our employees say about working with us on DOU. What is your new project? Domain: Venture Capital and Private Equity Principals Client Location: Israel Company size: 10-50 Founded in: 2016 What makes this project exciting? We’re looking for a senior engineer who can build AI native products on top of reliable, secure, high quality data systems. Someone who has experience shipping production level software for high trust workflows, understands data pipelines and data quality deeply, can deploy safe agentic systems, and knows how to design robust architecture that scales. This role is for someone who has shipped production software at scale, understands data pipelines and data quality deeply, and knows how to deploy AI systems that are useful, observable, and safe. You’ll work across the full stack: data ingestion, transformation, storage, APIs, product surfaces, AI workflows, agentic systems, and observability. What makes you a great fit You have strong production engineering judgment and can move quickly without compromising reliability, data integrity, and security: ● 8+ years building production software ● Strong experience with TypeScript, React, SQL ● Deep backend architecture, API, data modeling, and production debugging skills ● Significant experience with data pipelines, integrations, or data-heavy systems ● Experience building systems that handle sensitive, regulated, and high trust data ● Production experience shipping robust AI/LLM-powered features ● Strong understanding of evals, hallucinations, malformed outputs, retrieval quality, latency, cost, model drift, and provider risk ● Good judgment about when to use an LLM, when to use retrieval, when to improve the data foundation, and when deterministic code is the better answer ● Excellent written and verbal communication in English ● High ownership AI safety and security: ● You know how to build AI systems that are useful without being reckless. ● You understand prompt injection, permission boundaries, data exfiltration risk, secrets handling, audit logs, and human in the loop review. You treat model context as untrusted input and design agent systems with scoped tools, explicit permissions, logging, evals, and graceful failure modes. ● Security is non-negotiable. You should be comfortable with access control, Postgres RLS, PII handling, secrets management, audit trails, least privilege, secure integrations, and safe use of third-party APIs. You’ll be especially strong if: ● You have built sturdy data pipelines customer facing products rely on ● You care about data correctness before AI or dashboards depend on it ● You can trace a bad number across ingestion, transformation, database, API, UI, and AI context ● You think naturally in failure modes: stale data, duplicate events, schema drift, partial writes, bad joins, expired tokens, provider outages, and malformed model outputs ● You have worked in high trust data environments such as finance, investment, legal, healthcare, or enterprise saas ● You have experience with Supabase, Postgres RLS, Deno, Modal, embeddings, vector search, transcription, GPU workloads, or similar infrastructure ● You have worked with data validation, reconciliation, lineage, observability, or audit systems ● You have experience with AI evals, AI observability, agent testing, or red-teaming AI systems Your day-to-day in this position You will design and ship production-grade systems that combine software engineering, data infrastructure, and AI, including: ● Building secure, scalable full-stack product features ● Designing data models, APIs, integrations, and backend architecture ● Creating reliable data pipelines with strong validation and observability ● Shipping high value high trust AI/LLM-powered features ● Building safe agentic workflows with scoped tools, permissions, logging, evals, and failure handling ● Debugging issues across ingestion, transformation, database, API, UI, and AI context ● Designing systems with security, privacy, auditability, and observability Why work with us? People-first management with minimal bureaucracy A friendly company culture, proven by employees who choose to return Flexible working hours 29 days of PTO (18 working days per year pluse all national holidays) 10 paid recovery days Full financial and legal support for independent contractors Free English classes, with native speakers or Ukrainian teachers Dedicated HR support Our next steps ✅ Intro call with a Recruiter — ✅ Intro with the client — ✅ Test Task — ✅ Final client interview— ✅ Offer Originally posted on Himalayas

查找职位、比较要求,再准备申请

从你希望从事的职位或运用的技能开始搜索。调整地点和职业筛选,打开职位比较工作职责。如果没有结果,可以使用更短的关键词,或逐一移除筛选条件。

区分必备要求和优先条件,检查已列出的工作安排、薪资和地点。远程职位也可能要求特定居住国家、工作许可或工作时间重合。请向雇主确认职位信息和完整条件。

选择能够回应职位要求的真实经历,说明你的贡献,只使用能够证实的数字。遵循雇主的申请说明,并在提交前检查联系方式、文档内容和 PDF。

提交申请前的检查清单

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。