AI Engineering Lead

Why should you join dLocal?

dLocal enables the biggest companies in the world to collect payments in 40 countries in emerging markets. Global brands rely on us to increase conversion rates and simplify payment expansion effortlessly. As both a payments processor and a merchant of record where we operate, we make it possible for our merchants to make inroads into the world’s fastest-growing, emerging markets.

By joining us you will be a part of an amazing global team that makes it all happen. Being a part of dLocal means working with 1000+ teammates from 30+ different nationalities and developing an international career that impacts millions of people’s daily lives. We are builders, we never run from a challenge, we are customer-centric, and if this sounds like you, we know you will thrive in our team.

What’s the role?

As DCoder Lead, you will own the technical vision, development, and adoption of DCoder — dLocal’s internal AI-assisted coding platform. This role blends hands-on engineering, platform ownership, developer enablement, and strategic leadership across engineering teams.
You’ll act as the key technical referent for how AI-powered coding tools are designed, integrated, scaled, and governed across the software development lifecycle.

What will you be doing?

Own the architecture, roadmap, and evolution of DCoder, integrating with LLMs, CI/CD, repos, and engineering workflows.
Drive developer adoption through documentation, demos, training, and enablement materials.
Define best practices and guardrails for AI-assisted coding (prompt design, context management, evaluation, safety).

Partner with Engineering, Platform, Security, and Product to align priorities and deliver impact.
Ensure DCoder operates reliably at scale — balancing performance, cost, security, and usability.
Gather continuous feedback from developers and iterate quickly on improvements.
Establish governance and standards around responsible AI usage in SDLC workflows.

What skills do you need?

Real software development experience: 5+ years hands-on engineering, having shipped and operated production code; fluency with Git, code review, CI/testing, and modern backend/front-end stacks.
Proven experience applying AI and LLM-based systems in real-world environments, including assistants and agents used at scale.
Solid understanding of AI system technology (LLMs, APIs, orchestration, prompt/context management, evaluation, cloud platforms).
Practical knowledge in building and deploying microservices and integrating third-party APIs and AI services.
Experience with monitoring applications in production.
Hands-on experience with AWS; GCP is a plus.
Leadership & Product
Product management or equivalent ownership experience, preferably in developer tools, platforms, AI/ML systems, or infrastructure.
Experience leading and developing engineers, providing technical direction, prioritization, and support while fostering high standards and autonomy.
Technical depth plus product judgment: Ability to read/reference code and architecture, prototype to de-risk ideas, and define clear success criteria.

Strategy, Metrics & Adoption

Data-driven execution: Comfortable designing metrics, running experiments, and using telemetry to inform prioritization and validate changes.
Strong ability to work in close partnership with Product, contributing to discovery and prioritization.