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Madrid, Comunidad de Madrid, España
Hybrid
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 engineering teams to align roadmaps, manage technical debt, and ensure platform capabilities meet business needs.
Continuous Improvement: Track industry trends in platform engineering and applied AI, identify automation opportunities, and pilot innovations that keep our platform ahead of scale and compliance demands.
Bachelor's degree in Computer Science, Software Engineering, or a related field.
5+ years of professional experience building backend, platform or DevOps systems, with strong programming proficiency in at least one of TypeScript/Node.js, Go or Python — and willingness to work across all three.
Hands-on experience with containerization & orchestration (Docker, Kubernetes) and modern CI/CD pipelines (GitHub Actions, Argo Workflows/ArgoCD, Jenkins or similar) on a major cloud provider (AWS preferred).
Experience building internal tooling, reusable SDKs/libraries, or platform components used by other engineering teams — a builder profile, not only an operator.
Practical, demonstrable adoption of AI-assisted development (Claude Code, Copilot, Cursor or similar) in your daily workflow, and genuine interest in building with LLMs and agents.
Automation mindset: able to spot manual, repetitive engineering work and turn it into platform capabilities.
Advanced English; able to articulate complex ideas to both technical and non-technical stakeholders.