What will I be doing?
- AI for Developer Acceleration:
- Build AI-powered tools to enhance each stage of the SDLC: from code generation and code reviews to testing, documentation, and deployment.
- Develop internal assistants and copilots to reduce cognitive load and empower developers to move faster with fewer manual steps.
- Automate repetitive development and operational tasks (e.g., writing IaC, generating release notes, updating documentation).
- Research & Prototyping:
- Investigate GenAI solutions (e.g., GitHub Copilot, CodeLlama, GPT-Engineer) to improve CI/CD workflows and eliminate friction in delivery pipelines.
- Design, benchmark, and deploy AI-driven solutions that reduce lead time, increase deployment frequency, and enhance reliability.
- Explore custom model fine-tuning and retrieval-augmented generation (RAG) approaches when needed.
- Platform & Delivery Innovation:
- Prototype features like AI-driven deployment optimizations, cost-aware autoscaling, or predictive incident resolution.
- Embed AI into DevOps processes to identify bottlenecks, automate root cause analysis, and surface continuous delivery insights.
- Collaborate with SRE and developer experience teams to evolve our Internal Developer Platform (IDP) with intelligent automation.
- Cross-Team Collaboration & Knowledge Sharing:
- Partner with engineering, DevOps, and product teams to identify key pain points and deliver impactful AI interventions.
- Share findings through workshops, whitepapers, and internal demos to scale learnings across the organization.
What skills do I need?
- Technical Expertise:
- Solid understanding of the full Software Development Lifecycle (planning, coding, testing, releasing, monitoring).
- Experience with CI/CD systems and infrastructure automation (Terraform, Kubernetes, Ansible).
- Proficiency in Python and scripting (e.g., Bash, Go); ability to work across AI, infrastructure, and tooling codebases.
- Experience working in cloud environments (AWS/GCP) and with container orchestration (Docker, Kubernetes).
- AI/ML Knowledge:
- Practical experience with LLMs and code-generation tools (e.g., Codex, StarCoder, Claude, GPT family).
- Ability to prototype, benchmark, and deploy AI solutions that improve developer workflows.
- Familiarity with prompt engineering, fine-tuning, or RAG pipelines is a plus.
- Mindset & Communication:
- Research-driven and curious: you’re always testing new ideas, tools, and approaches.
- Capable of explaining complex AI solutions to cross-functional teams.
- Strong problem-solving skills: you identify inefficiencies and use AI to unlock new delivery velocity.
- Bonus Points For:
- Published work or open-source contributions in AI applied to software engineering.
- Experience building or contributing to internal developer platforms (IDP).
- Experience applying AI to improve software quality, deployment safety, or observability.
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What We Do
dLocal started with one goal – to close the payments innovation gap between global enterprise companies, and customers in emerging economies. We have over 900 payment methods, in more than 40 countries.
With the ability to accept local payment methods and facilitate cross-border fund settlement worldwide, our merchants reach billions of underserved consumers in the high-growth markets of Africa, Asia, and Latin America. dLocal offers the ideal payment solutions for global commerce:
Payins: Accept local payment methods
Payouts: Compliantly send funds cross-border
Defense Suite: Manage fraud effectively
dLocal for Platforms: Unify your platform’s payment solution
Local Issuing: Localize payments for your gig-economy workers, suppliers, and partners







