- As a Platform Engineering Technical Referent at dLocal, you will be a senior technical reference for how we design, build and evolve our internal developer platform, our CI/CD automation, and our AI-native software delivery stack
- Your mission is to enable every engineering team at dLocal to take features from idea to production in a reliable, automated and increasingly AI-assisted way
- Today our AI-SDLC platform automates a significant share of development tasks across 60+ engineering teams, and our delivery platform is being re-architected from the ground up on a modern cloud-native stack; you will help drive both forward, defining best practices and architectural patterns as complexity and business demands grow
- Platform Engineering: Design, build and maintain core components of our internal developer platform — APIs, CLIs, web surfaces and golden paths — enabling product teams (and AI agents) to build and ship services in a self-service, standardized way
- CI/CD Automation: Evolve our build and deployment platform on top of Kubernetes and GitOps tooling,



replacing legacy pipelines with a declarative architecture that scales across environments and regions, reducing manual work and errors
- AI-Native SDLC: Contribute to the architecture of our AI engineering stack — coding agents, orchestration flows, automated code review and automated vulnerability patching — helping define what gets automated and how AI is embedded across the software development lifecycle
- Architecture & Standards: Champion best practices, standards, and author and review RFCs that impact how we build and deploy code company-wide. For example: platform contracts, observability, security, and performance best practices
- Mentorship & Leadership: Serve as technical referent for a multi-disciplinary platform team; coach engineers, run architecture reviews, and foster a culture of continuous improvement
- Cross-Functional Collaboration: Work with Security, Infrastructure and product enginee

📌 Platform Architect (Madrid)
🏢 dLocal
📍 Madrid