Join dLocal and Shape the Future of Payments!At dLocal, we empower leading global enterprises to streamline payment processing across 40 emerging markets. Our innovative solutions not only enhance conversion rates but also facilitate seamless payment expansion, helping our clients tap into the fastest-growing markets worldwide. As both a payment processor and merchant of record, we enable businesses to thrive in these dynamic environments.By becoming part of our team, you will collaborate with over 1,000 diverse professionals from 30+ nationalities, shaping an international career that positively impacts millions of lives every day. We are a community of builders who embrace challenges, prioritize customer satisfaction, and are driven to innovate. If this resonates with you, we are excited for you to join us!About Agentic Development at dLocalOur Agentic Development product is designed to accelerate software delivery by transforming well-defined requirements into ready-to-review pull requests, tightly integrated with our Software Development Life Cycle (SDLC). This strategic initiative aims to reduce lead times, enhance quality and consistency, and empower developers to focus on higher-value tasks.Role OverviewWe are looking for an experienced AI Product Manager to lead and expand our Agentic Development product. Your primary objectives will be to enhance capabilities, foster product adoption, and significantly reduce development lead times. You will collaborate with teams across Development Productivity, Engineering, AI, Security, and other domains to shape the product roadmap, implement improvements in planning, execution, and validation workflows, and establish the necessary telemetry and change management for enterprise-wide adoption. This role demands hands-on software development experience, alongside expertise in product management and applied AI.Desired MindsetWe value a builder-first mentality in our Product Managers who are outcome-driven, focused on measurable improvements in lead time and quality. You should possess a systems-thinking approach that connects upstream inputs to downstream results, and a pragmatic understanding of AI that clarifies where agents excel and where they fall short, enabling safe instrumentation, gating, and iterative processes.
Jul 16, 2025