Global Engineering Director | People Tech

Other Palo Alto, São Paulo Today

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Listed via Greenhouse · Redirects to Nubank's careers page

Job Description

About Nubank

Nu is the world's largest digital banking platform outside of Asia, serving over 127 million customers across Brazil, Mexico, and Colombia. Guided by its mission to fight complexity and empower people, Nu caters to customers' complete financial journey — promoting financial access with responsible lending and transparency. Recognised by Time 100 Companies, Fast Company's Most Innovative Companies, and Forbes World's Best Banks, Nu is now entering its next growth cycle: accelerating internationalisation outside Latin America and expanding into new verticals beyond financial services.

About the Team

The People Analytics Technology Operations (PATO) team is redefining what People & Culture infrastructure looks like for a company operating at global scale with an AI-first mandate. We don't run HR software — we build the systems that make HR itself obsolete in its traditional form. Our work touches every Nubanker, every country, every moment of the employee lifecycle. We are the internal frontier lab for agentic people systems.

About the Role

Here is the core question this role exists to answer: if you were designing People & Culture infrastructure from scratch today — knowing that AI agents will run most operations, humans will audit rather than execute, and the channels and surfaces workers interact with don't fully exist yet — what would you build?

This isn't a rhetorical question. It's the actual brief.

The SaaS era of HR technology is being disrupted faster than most incumbents can adapt. Workday, SAP, ServiceNow — products built for a world of human workflows and form-based interfaces — are structurally ill-equipped for an agent-native operating model. The real competitive moat in this next era won't be features. It will be the depth of integration within a specific domain, and the quality of the data and reasoning layer that sits beneath it. We have the rare opportunity to build that solution — purpose-built for the People & Culture domain — inside one of the most technically ambitious companies in the world.

As Global People Data & Tech Director, you will lead the effort to design and build this from the ground up. You will define what the agentic HR stack looks like: the data models that make agents actually useful, the orchestration layer that lets them act with minimal human friction, the audit surfaces that let people stay in control without becoming bottlenecks, and the foundational platform that scales to 40+ markets without scaling the team that builds it. Agentic development practices aren't a side methodology here — they are how this organisation will operate. You build with agents, you build for agents, and your team stays lean precisely because of it.

This role isn't for someone who has deep experience with HR software. It's for someone who looks at HR software and sees an industry ripe to be rebuilt. You are a product and infrastructure thinker who happens to care deeply about the employee experience — and who has the technical depth and organisational leadership to translate that vision into production systems used by hundreds of thousands of people.

Key Responsibilities

Define the Agent-Native HR Stack

Design the architecture for a People & Culture platform where agents are first-class citizens: capable of executing hiring, onboarding, payroll, compliance, and performance workflows with minimal human intervention.
Define the human-in-the-loop model — which decisions require human review, through what interfaces, with what level of latency — so that oversight is meaningful rather than ceremonial.
Identify and kill the workflows that should no longer exist at all.

Build the Data Foundation

Architect the People data layer that will serve as the substrate for agent reasoning, predictive analytics, and LLM-powered insight generation for the next decade.
Ensure the data model is jurisdiction-aware from day one — built to accommodate the legal, cultural, and operational variance of 40+ markets without requiring structural rework per country.
Drive the transition from fragmented HR data silos to a unified, real-time, auditable data layer that agents and analysts can trust equally.

Build With and For Agents

Apply agentic development practices to your own team's engineering process — using agents to write, test, review, and deploy code so that headcount does not scale linearly with product scope.
Lead the development of real-time AI-powered employee experiences: intelligent copilots, proactive guidance systems, and autonomous support channels that resolve needs before they become tickets.
Advance Nubank's application of large language models to unstructured People data — feedback, communications, performance narratives — turning qualitative signal into structured organisational insight.

Own the Platform Vision

Define the comprehensive HR platform roadmap — what we build, what we integrate, and what we deliberately do not own — with a bias toward deep integration over broad coverage.
Ensure the platform is designed for global scale from the start: multi-currency, multi-jurisdiction, multi-language, and operable across legal entities without per-country engineering investment.
Bridge strategic vision with hands-on execution, staying close enough to the codebase and architecture to make credible decisions and earn the trust of your engineering team.

Lead the Organisation

Build and lead a high-performing, deliberately lean team that punches well above its headcount because it builds and operates with agents.
Develop senior technical leaders who can own domains end-to-end, reducing coordination overhead and enabling faster iteration.
Foster a culture of intellectual honesty — one that questions inherited assumptions about how HR technology should work, and is willing to discard anything that doesn't hold up.

Qualifications & Skills

What We're Looking For

We are not looking for someone who has spent their career in HR technology. We are looking for someone who has built consequential software systems, who thinks seriously about agents and automation, and who is intellectually excited by the opportunity to apply that background to a domain that is fundamentally underbuilt.

Required

10+ years in software engineering and technology leadership, with demonstrated experience owning large-scale production systems from architecture through operation.
Deep fluency in data architecture and data modelling — the ability to design canonical data structures that remain coherent as business complexity grows across jurisdictions and entity types.
Hands-on experience building with or designing for agentic systems: familiarity with LLM-based reasoning, tool use, multi-agent orchestration, and the failure modes that come with autonomous execution.
Experience leading platform or infrastructure products — systems used by other teams and applications, not just end users — with the taste and discipline that entails.
Proven ability to scale impact without scaling headcount: through leverage, tooling, great architecture, and a culture that defaults to automation before process.
Strong engineering management skills, including the ability to hire, develop, and retain senior technical talent and engineering leaders.

Valued

Experience building products that operate across multiple legal jurisdictions — especially products where regulatory variance is a first-class design constraint, not an afterthought.
Background in developer platforms, internal tooling, or B2B SaaS — contexts where you have thought carefully about API design, data contracts, and integration depth.
Familiarity with the People & Culture domain — not as a practitioner, but as a product builder who has spent time understanding what HR teams actually do, where the friction lives, and what automation can and cannot replace.
Experience operating within a high-growth technology company where ambiguity is the norm and the product surface changes faster than any roadmap.

Core Leadership Skills

Business Acumen: Drives strategic alignment by reading market dynamics, spotting where incumbents are structurally vulnerable, and translating that into build-vs-integrate decisions with long-term leverage.
Communication: Moves between technical depth and executive narrative fluently — able to defend architectural choices with an engineer and explain the same decision to a board.
Agile Adaptability: Leads in conditions of genuine uncertainty, treating early product iterations as learning instruments and calibrating direction based on evidence rather than original conviction.