Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.
Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability.
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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.
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.
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.
To maintain a consistent and fair process for every candidate, Nu does not provide individualized technical feedback. See how our policy works here
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