Head of Developer Productivity

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 opportunity? We are looking for a Head of Developer Productivity to lead the strategy, execution and continuous improvement of the tools, workflows and AI-powered systems that make our engineers more productive every day.   In this role you will own the Developer Productivity (DevPro) vision and multi-year roadmap inside Cloud Platform. You will lead a team composed of several specialized sub-teams — including an AI software-engineering agent squad, an internal frameworks and libraries team, a CI/CD and platform tooling team, and a shared applications team — and you will be accountable for how all of them come together to reduce engineering friction, improve delivery metrics, and embed AI into every phase of the Software Development Lifecycle (SDLC).   This is an AI-leadership role. We already have a production ecosystem of AI agents that automate coding, planning, code review, and vulnerability remediation across the SDLC — and we are actively expanding it. Your mission is to scale these capabilities, drive adoption across the engineering organization, and make AI the default way engineers work at dLocal.   You will partner closely with AI Labs, AI Engineering, Platform, SRE, Security and Product teams to shape how AI agents, engineering metrics, internal frameworks and our Internal Developer Platform converge into a cohesive, high-leverage developer experience. What will you do?

AI Strategy & Agent Ecosystem

• Own the roadmap and prioritization for AI-powered developer workflows across the full SDLC: autonomous code generation agents, AI planning agents that break down epics into developer-ready tasks, AI code-review tools, AI-assisted test generation, automated vulnerability remediation, and AI-driven incident investigation.

• Act as the product owner for the AI agent ecosystem: define use cases, success metrics, adoption targets, safety policies, and rollout strategy. Measure end-to-end automation rates (from ticket creation to merged PR) and continuously raise the bar.

• Drive the architecture and integration of AI agents with existing developer tools — issue trackers, source control, CI/CD pipelines, IDEs, observability platforms, and the Internal Developer Platform — so that AI is embedded contextually where engineers already work, not bolted on as a side tool.

• Champion the adoption of Model Context Protocol (MCP) and similar standards to connect AI agents with internal documentation, service catalogs, logs, and production data, enabling agents that don't just read code but understand the full operational context.
  

Engineering Metrics & DORA

• Define, build and operate a unified engineering metrics platform that calculates DORA metrics (Lead Time for Changes, Deployment Frequency, Change Failure Rate, Mean Time to Recovery) from real data across source control, issue tracking and deployment systems, with consistent and auditable definitions.

• Set organization-wide targets for engineering delivery metrics and use them to identify bottlenecks, prioritize investments, and demonstrate the measurable impact of Developer Productivity and AI initiatives.

• Integrate AI-adoption metrics (automation rate, AI-generated vs. human-generated code, agent throughput, first-pass approval rate) into the engineering metrics platform so leadership can track the ROI of AI investments alongside traditional delivery health.

• Deliver self-service dashboards and automated reporting so that every team, vertical, and executive has real-time visibility into their productivity trends.

 

Developer Experience & Internal Platform

• Own the developer experience strategy: run SPACE-framework developer satisfaction surveys, track Customer Effort Scores, and use qualitative and quantitative signals to continuously improve how engineers interact with the platform.

• Champion the evolution of the Internal Developer Platform (service catalog, self-service actions, golden-path templates, scaffolding) so that creating a new service, deploying to production, or triggering an AI agent is a frictionless, self-service experience.

• Lead the internal frameworks and libraries team, ensuring that shared application frameworks across languages (Go, Java, JavaScript/TypeScript) are standardized, well-maintained, and continuously improved — reducing boilerplate and letting engineers focus on business logic.

• Oversee the CI/CD platform team: GitHub Actions workflows, container builds, GitOps deployments, release governance, and environment management — ensuring pipelines are fast, reliable, and increasingly AI-augmented.
  
  

People Management & Enablement

• Manage, grow and inspire a multi-squad Developer Productivity team (currently ~15 engineers across sub-teams focused on AI agents, internal frameworks, CI/CD tooling, and shared applications). Hire and develop technical leaders who think AI-first.

• Lead change management and enablement for AI adoption across engineering: create onboarding programs, RFCs, internal talks, documentation, and hands-on workshops that help every team understand and leverage AI tools effectively.

• Facilitate cross-team collaboration: gather feedback from Engineering Managers, Staff Engineers and ICs; translate pain points into actionable initiatives; communicate trade-offs and decisions clearly to both technical and non-technical stakeholders.

• Partner with Security and Compliance to embed secure-by-design practices into AI workflows, including clear policies for when AI agents can propose, implement, or auto-merge changes — especially for security-sensitive operations like vulnerability remediation.

Which skill do you need?

8+ years of experience in Software Engineering, Platform Engineering, DevEx or related roles, with 4+ years in a management or senior leadership position overseeing Developer Productivity, Developer Experience, Internal Developer Platform, or similar teams.

Strong people-management experience: track record of building, scaling and retaining high-performing engineering teams. Ability to coach engineers and managers toward technical leadership and create an environment where teams ship with high autonomy.

Demonstrated experience leading AI-powered developer-tools initiatives: you have shipped or product-managed AI coding agents, LLM-based code-review tools, AI planning assistants, or similar developer-facing AI products — not just experimented with them, but driven measurable adoption and impact at scale.

Deep understanding of DORA metrics and engineering-productivity measurement: you know how to define, instrument, and use Lead Time, Deployment Frequency, Change Failure Rate, and MTTR to drive decisions. Experience building or operating engineering metrics platforms is a strong plus.

Excellent communication and stakeholder-management skills: comfortable working with engineering leaders, individual contributors, security, product, and AI teams in a fast-moving, global organization.