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Lead AI Engineer - Productivity Systems

Nubank · São Paulo

RemoteEngineeringEngineerEngineerPosted Last week
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About this role

ABOUT NU Nu is the leading digital bank in Latin America, serving 135 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 We are looking for an engineer who has already built with AI in production. You have shipped LLM-powered systems (agents, copilots, RAG pipelines, or AI-driven automations), you know what breaks when they meet real users, and you know how to make them reliable enough for business-critical workflows. Your day-to-day is applied AI engineering: designing agentic workflows, integrating LLMs into internal tools and business processes, building evaluation and guardrail layers, and turning manual, high-friction workflows into AI-assisted ones that thousands of Nubankers depend on. This is not an infrastructure role. You will not spend your days on Terraform, IAM policies, or email deliverability. Cloud fluency helps, but the core of this job is the AI layer - prompts, context, agents, evaluations, integrations - and the product judgment to know where AI genuinely helps versus where deterministic automation is the right answer. KEY RESPONSIBILITIES Applied AI & Agentic Systems - Design, build, and ship LLM-powered agents and workflows that automate complex internal processes end-to-end. - Work hands-on with frontier models and the modern AI stack: tool/f

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