About the Role
At Nubank, AI is not a "bolt on" feature. It is existential to our next phase of growth. We are transforming into an AI native company, where intelligent systems don't just support our products; they define them. As a Lead Software Engineer in AI Agents & Orchestration, you will be at the heart of this metamorphosis.
You will lead the technical direction for embedding Generative AI and LLMs into the lives of over 130 million customers. This role isn't about working in an isolated lab; it's about building production grade, agentic workflows and RAG pipelines that scale across multiple markets. You will leverage our specialized GenAI Platform including: inference services, evaluation frameworks, and orchestration layers to move from experimentation to global impact at "Nu-speed."
Responsibilities
- Lead the AI Architecture: Define the technical roadmap for AI native applications, ensuring our LLM integrations are scalable, cost effective, and highly reliable.
- Build Agentic Workflows: Design and implement complex agentic systems and RAG patterns that provide hyper-personalized financial experiences.
- Drive Engineering Excellence: Set the "canonical" standards for AI development at Nu, promoting reusable components
- Collaborate Across Surfaces: Partner with Product, Design, and Data Science to embed LLM capabilities across mobile, web, and internal operations tools.
- Optimize for Quality: Establish rigorous evaluation (QA) and monitoring practices for AI outputs to ensure safety, accuracy, and human in the loop integrity.
- Mentor and Scale: Actively participate in hiring and mentoring, fostering a high performance culture within our internal AI Academy and technical guilds.
- Strategic Decision Making: Balance short term delivery with medium term platform stability, making critical tradeoffs on model selection and system complexity.
Required Qualifications
- Technical Leadership: Track record as a lead delivering high impact, large scale software systems.
- AI First Mindset: Professional experience implementing LLMs, Generative AI features, or RAG patterns in a production environment.
- Full Stack Thinking: Proficiency in building maintainable codebases and API designs that bridge model inference layers with userfacing surfaces.
- Complex Problem Solving: Experience navigating ambiguous projects that require coordination across multiple business units and stakeholders.
- Strategic Acumen: Ability to link technical AI initiatives to core business drivers like operational efficiency and customer acquisition.
Nice to Have Qualifications
- Ecosystem Experience: Familiarity with PyTorch, TensorFlow, or Python based AI toolchains.
- Modern Stack: Experience with Flutter (Mobile) or cloud-native infrastructure (AWS/Azure).
- Domain Expertise: Background in FinTech or highly regulated industries where "Responsible AI" and data privacy are paramount.
- Global Scale: Experience scaling products across diverse international markets and languages.