Why Join dLocal?
dLocal is the financial infrastructure powering global commerce in the world's fastest-growing markets. The biggest companies in the world trust us to unlock growth in 60+ countries across emerging markets—moving money where others see complexity. We don't just process payments; we are architects of payment ecosystems and partners in our customers' expansion. You'll work alongside 1,300+ teammates from 40+ nationalities and tackle global challenges from day one.
What's the opportunity?
We are looking for a DevOps Engineer, Technical Referent to join our team! You will be the technical reference of a talented team that works on mission-critical applications for big customers like Netflix, Amazon, Nike, Facebook, Google & more. Beyond hands-on engineering, you will set the technical direction of our platform, mentor other engineers, and lead our shift towards an AI-first way of building, shipping, and operating software.
What will I be doing?
- Act as the team's technical referent: drive architectural decisions, set engineering standards, and mentor engineers to raise the technical bar across the organization.
- Champion an AI-first approach to platform engineering: embed AI agents and assistants across the software delivery lifecycle, and build the skills, plugins, and MCP integrations that make them first-class citizens of our workflows.
- Optimize developer productivity by designing and implementing self-service platforms and automation frameworks that streamline software delivery.
- Improve software deployment processes by enhancing CI/CD pipelines and ensuring scalable, reliable, and secure releases.
- Enhance the developer experience through workflow automation, internal developer platforms, and self-service tooling.
- Automate infrastructure provisioning and configuration management, promoting a declarative and automated approach to operations.
- Architect scalable and resilient cloud-based solutions, ensuring best practices in security, observability, and cost optimization.
- Develop and maintain internal tooling and automation — increasingly AI-assisted and agent-driven — to improve efficiency and streamline operations.
- Monitor, troubleshoot, and optimize platform performance using observability and monitoring solutions.
- Evaluate emerging AI models, agents, and tools, and define guidelines for their secure, responsible, and effective adoption across engineering teams.
- Advocate for modern software delivery practices, including Infrastructure as Code, GitOps, cloud-native architectures, and AI-augmented engineering.
Information regarding benefits, perks, and specific growth opportunities was not provided in the job posting.
What skills do I need?
- Proven experience acting as a technical referent or lead: driving technical decisions, mentoring engineers, and influencing beyond your own team.
- AI-first mindset: you use AI agents and coding assistants as a natural part of your daily workflow, and you understand the building blocks of the ecosystem — models, agent skills, plugins, and protocols such as MCP (Model Context Protocol).
- Hands-on experience integrating AI into engineering workflows, such as agentic automation, custom MCP servers, or AI-assisted CI/CD.
- Experience in designing and managing CI/CD pipelines with automation and deployment tools.
- Proficiency in Infrastructure as Code (IaC) and configuration management frameworks.
- Strong understanding of container orchestration and cloud-native architectures for scalable application management.
- Experience building and managing internal developer platforms and self-service infrastructure solutions.
- Expertise in cloud environments and best practices for security, scalability, and cost efficiency.
- Scripting and automation skills using programming languages for workflow optimization.
- Proficiency in monitoring, logging, and observability solutions to ensure system reliability.
- Knowledge of modern software delivery methodologies, including GitOps, automated testing, and continuous deployment.
- Security-first mindset, ensuring compliance and best practices across cloud, infrastructure, and AI tooling.
