远程工作雷达

软件工程师负责人 (加密货币, SV) - 美国 - IC6 - 2026

Lead Software Engineer (Crypto, SV) - US - IC6 - 2026

开发工程未标注地域
公司Nubank
薪资未公开
工作地点Palo Alto
地域资格未标注地域
时区要求无特别要求
用工类型FullTime
发布时间2026-07-19
数据来源Ashby
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关于Nu

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。该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,赋能人们”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

关于职位

Nu正在构建安全、合规的加密货币基础设施,以扩大拉丁美洲数百万人的金融准入。作为这一努力的一部分,我们通过一个内部对话式AI平台,根据客户的组合、风险偏好、市场状况和财务行为,为客户提供个性化、数据驱动的加密货币体验。

我们正在寻找一位高级软件工程师,其工作位于加密货币产品、客户数据和应用AI集成的交汇点。你将与核心加密货币工程团队紧密合作——利用并贡献区块链集成、钱包和组合数据以及链上信号——并将这些转化为丰富、可靠、个性化的上下文,由我们的AI平台合作伙伴构建的对话式和代理式体验所驱动。

你将设计和运营数据管道和集成层,使加密货币数据在数百万不同背景、风险承受能力和加密知识水平的客户中可使用、安全且有意义。你将与平台侧的机器学习工程师合作,他们带来建模和检索的专业知识,而你则负责他们所依赖的加密货币数据基础。

你将负责

- 与区块链协议和核心加密货币系统集成,与核心加密货币团队合作,获取组合、交易和市场数据。

- 设计和构建数据管道,将原始加密货币和客户数据转换为结构化、可靠的AI驱动体验的上下文。

- 与AI平台团队及其机器学习工程师合作,定义数据契约、工具接口和上下文模式。

查看英文原文

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

ABOUT THE ROLE

Nu is building secure, compliant crypto infrastructure that will expand financial access for millions of people across Latin America. As part of that effort, we're bringing personalized, data-driven crypto experiences to our customers through an internal conversational AI platform which is powered by their portfolio, risk appetite, market conditions, and financial behavior.

We're looking for a Lead Software Engineer who sits at the intersection of crypto products, customer data, and applied AI integration. You'll work closely with our core crypto engineering team — leveraging and contributing to blockchain integrations, wallet and portfolio data, and on-chain signals — and turn that into rich, reliable, personalized context that powers conversational and agentic experiences built by our AI platform partners.

You'll design and operate the data pipelines and integration layers that make crypto data usable, safe, and meaningful at scale for millions of customers with different profiles, risk tolerances, and levels of crypto knowledge. You'll partner with ML engineers on the platform side, who bring the modeling and retrieval expertise, while you own the crypto data foundation they build on.

YOU'LL BE RESPONSIBLE FOR

- Integrate with blockchain protocols and core crypto systems, collaborating with the core crypto team, to source portfolio, transaction, and market data.

- Design and build data pipelines that transform raw crypto and customer data into structured, reliable context for AI-driven experiences.

- Partner with the AI platform team and their MLEs to define data contracts, tool interfaces, and context schemas that support personalized, conversational crypto experiences.

- Model and reason about customer profiles — risk appetite, portfolio composition, crypto literacy, and behavior — to drive relevant, personalized insights.

- Ensure data freshness, consistency, and correctness for information flowing into customer-facing conversational surfaces maintained by another team.

- Build in safeguards against unsafe or misleading outputs (e.g., stale data, untrusted market/portfolio data, hallucinated financial claims).

- Operate these pipelines and integrations at scale and with the reliability expected of customer-facing financial infrastructure.

- Collaborate with product, compliance, and the AI platform team to ship personalized crypto features responsibly.

WE ARE LOOKING FOR A PERSON WHO HAS

Required

- Experience building data pipelines and integration layers that connect backend/product data to AI-driven systems (context engineering, tool/function calling) — collaborating with ML engineers rather than owning model training.

- Solid understanding of blockchain concepts and crypto products (wallets, portfolios, transactions, on-chain data), with the ability to integrate deeply with protocols and core crypto infrastructure.

- Experience working with customer data and behavior to drive personalization (segmentation, risk profiling, usage patterns).

- Strong distributed-systems fundamentals — experience designing and operating data pipelines and services at scale (throughput, consistency, failure handling, freshness, reliability), rather than expertise tied to a specific programming language.

- Comfort working as a cross-team interface — translating a platform team's integration needs into clear data contracts and APIs.

- Awareness of the risks of exposing financial data to LLM-driven surfaces (data integrity, injection risks, appropriate guardrails).

Nice to have

- Experience with specific blockchain protocols (Ethereum, Bitcoin, Solana) and their data/integration patterns.

- Prior work integrating with RAG systems or agent tooling in a regulated or high-stakes domain.

- Experience in fintech, payments, or financial services with personalization or recommendation systems.

- Familiarity with vector databases, embeddings, or context-retrieval infrastructure.

- Experience partnering with conversational AI or LLM platform teams as a data provider.

Location: Palo Alto, United States

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.

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