资深软件工程师
Staff Software Engineer
Nu 是拉丁美洲领先的数字银行,为巴西、墨西哥和哥伦比亚的 1.4 亿客户提供服务。公司通过利用数据和专有技术,开发创新产品和服务,引领行业变革。
以对抗复杂性、赋能人为使命,Nu 为客户完整的金融旅程提供服务,通过负责任的贷款和透明度促进金融包容性和进步。公司由高效且可扩展的商业模式驱动,结合低成本服务与不断增长的回报。
Nu 的影响力已获得多项奖项的认可,包括《时代》100 家最具影响力公司、《快公司》最具创新力公司以及《福布斯》全球最佳银行。
访问我们的机构页面 https://www.nu.com/2026-en
在 Nubank,软件工程师处于数据、智能和规模的交汇点。我们构建每天处理数百万决策的系统,从欺诈检测到信用建模,而且越来越多地借助人工智能实现这一目标。机器学习嵌入到我们的核心产品中:在风险评估、个性化体验以及大规模自动化决策方面。这里的工程师不仅仅使用人工智能功能;他们还参与塑造智能系统的构建、部署和生产环境中的维护。
我们以工程严谨性、自主性和对影响力的深度关注来实现这一切。我们的工程师在全栈范围内工作:设计数据管道和架构,将机器学习模型部署并维护在生产环境中,以及构建支撑我们产品的分布式系统和平台。我们重视能够快速行动、独立运作、对自身决策负责到底,并对质量和工艺设定高标准的小型团队。
我们在整个技术栈中追求最先进的软件开发实践。虽然我们重视熟悉我们技术的候选人,但我们相信加入 Nubank 的工程师将与我们的团队一起学习和成长:
- 主要用 Clojure 编写的水平可扩展微服务,利用函数式编程和六边形架构
- 高吞吐量的事件驱动架构,用于服务间通信
- 持续集成和部署到云原生基础设施
- 基于 Datomic 构建的分布式事务系统,用不可变数据和强一致性建模复杂的业务领域
- 基于 ETL/ELT 最佳实践构建的现代数据平台,具备强大的监控和可观测性
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ABOUT NU
Nu is the leading digital bank in Latin America, serving 140 million customers across Brazil, Mexico, and Colombia. The company has been leading an industry transformation by leveraging data and proprietary technology to develop innovative products and services.
Guided by its mission to fight complexity and empower people, Nu caters to customers’ complete financial journey, promoting financial access and advancement with responsible lending and transparency. The company is powered by an efficient and scalable business model that combines low cost to serve with growing returns.
Nu’s impact has been recognized in multiple awards, including Time 100 Most Influential Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Banks.
Visit our Institutional Page https://www.nu.com/2026-en
At Nubank, software engineers sit at the intersection of data, intelligence, and scale. We build systems that process millions of decisions daily, from fraud detection to credit modeling and increasingly, we do this powered by AI. Machine learning is embedded across our core products: in how we assess risk, personalize experiences, and automate decisions at scale. Engineers here don't just consume AI capabilities; they help shape how intelligence is built, deployed, and maintained in production.
We do it with engineering rigor, autonomy, and a deep focus on impact. Our engineers work across the full spectrum: designing data pipelines and architectures, deploying and maintaining ML models in production, and building the distributed systems and platforms that power our products. We value small, independent teams that move fast, own their decisions end-to-end, and hold themselves to a high bar for quality and craft.
We strive for state-of-the-art software development practices across our entire stack. While we value candidates familiar with our technologies, we're confident that engineers who join Nubank will learn and grow alongside our team:
- Horizontally scalable microservices written mostly in Clojure, leveraging functional programming and hexagonal architecture
- High-throughput event-driven architectures for inter-service communication
- Continuous Integration and Deployment into cloud-native infrastructure
- Distributed transactional systems built on Datomic, modeling complex business domains with immutable data and strong consistency
- Modern data platforms built on ETL/ELT best practices, with robust monitoring and observability
OUR SOFTWARE ENGINEERS
- Work with large scale distributed systems
- Collaborate with building microservices
- Design, build and maintain robust data pipelines, distributed systems and ML-enabled solutions, ensuring reliability, scalability and performance at scale
- Deploy and maintain ML models in both batch and real-time scenarios, integrating them with other systems and monitoring through operational and business metrics
- Lead data and engineering projects end-to-end — from requirements gathering and stakeholder alignment to delivery and iteration
- Contribute to the design, documentation, maintenance and optimization of our data codebase, platforms and tooling
- Translate business needs into data products and technical solutions aligned with Nubank's architecture and long-term strategy
- Partner with technical and business stakeholders to define strategies and deliver high-impact solutions
- Share knowledge, mentor peers and contribute to engineering and data literacy initiatives across Nubank
WHAT WE'RE LOOKING FOR
- Programming experience in one or more general-purpose languages (e.g. Python, Clojure, Scala, Java)
- Familiarity with analytical data environments and data engineering concepts: pipelines, ETL/ELT, data modeling and storage
- Understanding of ML model lifecycle, from training and evaluation to deployment and monitoring
- Familiarity with distributed systems, microservices and asynchronous architectures
- Strong communication skills to collaborate with both technical and business stakeholders
- Passion for building high-quality software and data products
NICE TO HAVE
- Experience with cloud platforms such as AWS, GCP or Azure
- Knowledge of data architecture patterns (Data Lake, Data Warehouse, Data Mart)
- Familiarity with ML frameworks and feature engineering pipelines
- Experience with data visualization tools (Looker, Power BI, Tableau or similar)
- Knowledge of software engineering best practices: testing, clean code, documentation
Our Benefits
- Chance of earning equity at Nubank
- Food/Meal Card (Vale-Refeição and/or Vale Alimentação)
- Public Transportation Commuting Benefit (Vale-Transporte)
- NuCare – Psychological, Financial and Legal Assistance Program
- Life Insurance, Medical Plan and Dental Plan
- NuLanguage – Language Course Program
- Nucleo – Our learning platform
- Extended Parental Leave, Daycare Allowance and Parental Consultancy
- Work-from-home Allowance
- Gym Partnerships
- 30 days of paid vacation
- Relocation Assistance Package, if applicable
WORK MODEL
Hybrid 2–3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration.
For more details, visit building.nubank.com/nu-hybrid-work-model/ http://building.nubank.com/nu-hybrid-work-model/
Our recruitment process may involve the use of artificial intelligence–enabled tools, such as automated interview transcription and analysis, to support the evaluation process. Artificial intelligence is not used to make final hiring decisions; all decisions are made by human reviewers.