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Salary
≈ $58k – $135k per year (Estimated)
Location
Hybrid (Madrid, Barcelona, Spain, Buenos Aires, Argentina, Montevideo, Uruguay)
Seniority
Architect · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Aug 10, 2026. dLocal scores A on the Alion truth index.

Overview
Company
Impact
Profile match
dLocal is a payments company that lets global merchants accept and send payments in emerging markets through a single API, supporting local cards, bank transfers, cash vouchers and mobile wallets across Latin America, Africa and Asia. Founded in 2016 and listed on Nasdaq, it processes pay-ins and payouts for large technology, commerce and streaming companies. The company is headquartered in Montevideo, Uruguay.
Backed by Endeavor

What’s the opportunity?

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.

What will I be doing?

  • 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.

What skills do I need?

  • 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.

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