About Us

Nu is one of the largest digital financial platforms in the world, with more than 127 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.

Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human.

Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank. Visit our institutional page https://international.nubank.com.br/careers/

About the role

As a Staff Site Reliability Engineer for our Data Infra SRE team, you will be a strategic leader responsible for defining the future of reliability for our Data Platform. This role is pivotal in shaping the transition toward a Data Mesh architecture and executing the Archipelago evolution plan. Your primary goal is to ensure the scalability of our data infrastructure by moving beyond traditional SRE practices and investing heavily in intelligent automation. By leading the development of AI-driven reliability solutions, you will directly impact our ability to maintain high availability and performance across hundreds of business platforms and millions of global customers.

You'll be responsible for:

• Defining Strategic Evolution: You will lead initiatives to refine the strategic direction of the SRE team, ensuring the Data Platform infrastructure supports the company’s long-term decentralization goals and the Archipelago evolution plan.

• Designing Architectural Leadership: You will provide expert guidance for the design, implementation, and maintenance of highly reliable, scalable, and performant data systems.

• Pioneering AI-Driven Automation: You will champion the adoption of advanced automation frameworks such as Lang Graph and AI agents to autonomously resolve data platform crashes and coordinate incident responses.

• Implementing Proactive System Health: You will develop sophisticated anomaly detection and predictive analytics mechanisms to identify and prevent potential issues before they impact the business.

• Establishing Incident Protocols: You will lead the refinement of incident response protocols and post-incident analysis to drive continuous improvement in platform stability.

• Mentoring and Technical Culture: You will mentor other engineers, foster a culture of reliability engineering excellence, and take ownership of technical initiatives that eliminate toil and optimize resource utilization

We are looking for a person who has:

• Extensive Experience in SRE or Systems Engineering: A proven track record of leading complex technical initiatives and defining infrastructure strategies at a staff level or equivalent.

• Proficiency in Functional Programming and Big Data: Solid experience with Clojure and Datomic for backend systems, alongside Scala and Spark for high-volume data processing.

• Expertise in Cloud Infrastructure: Deep practical knowledge of managing mission-critical workloads on AWS using Kubernetes, Step Functions, Lambdas, and EC2.

• Experience Building Automation from the Ground Up: A demonstrated ability to innovate and build automation frameworks in greenfield environments, with a focus on implementing AI agents for operational efficiency.

• Advanced Knowledge of Reliability Practices: Experience defining and enforcing Service Level Objectives, managing system observability, and leading disaster recovery and capacity planning.

• Strategic Problem-Solving: The ability to translate complex architectural challenges into scalable software solutions while managing cost, performance, and security best practices.

Our SRE team is formally responsible for:

• Service Level Objectives (SLO) Management: Defining, monitoring, and enforcing SLOs for critical data platform services.

• System Observability: Implementing and maintaining comprehensive monitoring, logging, and tracing solutions across the data platform.

• Toil Reduction: Identifying and automating repetitive manual tasks to improve team efficiency and focus on strategic initiatives.

• Disaster Recovery and Business Continuity: Developing and testing disaster recovery plans to ensure the resilience of the data platform.

• Capacity Planning: Forecasting resource needs and planning for infrastructure scaling to meet anticipated demand.

• Performance Engineering: Optimizing system performance and addressing bottlenecks to ensure efficient operation.

• Security Best Practices: Implementing and advocating for security best practices within the data platform.

• Platform APIs: enabling alert management on virtually any service with simple interactions

Our Benefits

• Opportunity of earning equity at Nu

• Medical Insurance

• Dental and Vision Insurance

• Life Insurance and AD&D

• Extended maternity and paternity leaves

• Nucleo

• Our learning platform of courses

• Nu Language

• Our language learning program

• Nu Care

• Our mental health and wellness assistance program

• Extended maternity and paternity leaves

• 401K

• Saving Plans

• Health Saving Account and Flexible Spending Account

• Work-from-home Allowance

• Relocation Assistance Package, if applicable.

Work Model for this Role

Nubank operates in a hybrid model, where teams collaborate remotely and periodically come together for about one week of in-person sessions. For Canadian team members, these sessions typically take place in one of our hubs (Brazil, Mexico, Colombia, or the United States) and are communicated well in advance to allow proper planning, with travel support provided to ensure equitable access to these global collaboration opportunities.

Transparency in the use of AI

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.