About the Role

We are looking for an experienced software engineer to help evolve and operate Nubank's messaging platform and the infrastructure that supports asynchronous communication at scale.

This role sits in a team responsible for highly critical platform capabilities that support a wide range of internal systems across multiple business domains and countries. The platform operates in a large and complex environment, with hundreds of clusters, thousands of brokers, hundreds of thousands of topics, and very large daily data volumes across multiple AWS accounts.

At the Lead level, we are looking for someone who can independently own important technical problems, improve reliability and operability, and drive engineering decisions in partnership with the team. Kafka experience is desirable, but not required. Strong knowledge of distributed systems infrastructure, especially Kubernetes, networking, and AWS, is essential.
What You'll Be Responsible For

• Operate and improve large-scale messaging and platform infrastructure based on kafka used by critical systems across Nubank
• Contribute to the reliability, scalability, and performance of asynchronous communication platforms
• Help design and implement solutions for high-throughput, low-latency, and fault-tolerant systems
• Improve observability, automation, and operational excellence across the platform
• Support incident analysis, troubleshooting, and root cause remediation in production environments
• Optimize infrastructure usage and help drive efficiency and cost awareness across AWS-based environments
• Work on platform capabilities that enable safe growth in message volume, topic count, and cluster footprint
• Partner with other engineers and teams to evolve platform standards, tooling, and best practices
• Contribute to architectural discussions involving messaging, traffic patterns, service communication, and platform reliability

We Are Looking for a Person Who Has

Must-have

• Strong software engineering fundamentals and experience working with distributed systems in production.
• Solid experience with Kubernetes, networking, and AWS in large-scale or business-critical environments.
• Experience operating infrastructure-heavy platforms with high reliability and availability requirements.
• Ability to troubleshoot complex production issues across application, infrastructure, and network layers.
• Experience improving observability, automation, and operational tooling.
• Good understanding of scalability, resilience, performance, and failure isolation patterns.
• Ability to work autonomously on ambiguous technical problems and drive them to execution.
• Strong collaboration skills and ability to work across team boundaries.

Nice-to-have

• Experience with Apache Kafka or other messaging and streaming technologies.
• Experience with platform engineering, SRE, or infrastructure-focused backend engineering.
• Familiarity with multi-account AWS environments and large-scale cloud operations.
• Experience with high-throughput event-driven architectures.
• Experience balancing reliability, performance, and cost in production systems.

Our Benefits

• Total compensation includes base salary, RSUs and benefits. Base salary range: $210.000 - $252.000

• Health Insurance
• Life Insurance
• Pension Plan
• Extended maternity and paternity leaves
• Nucleo - Our learning platform of courses
• NuLanguage - Our language learning program
• NuCare - Our mental health and wellness assistance program
• Vacations

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.