About dLocal
dLocal provides financial infrastructure that powers global commerce in fast-growing markets. It enables companies to make payments across more than 60 emerging markets and supports their expansion.
Responsibilities
•Lead AI initiatives from problem definition through production delivery, coordinating with engineers and team leads
•Align scope, priorities and expectations with peers and business stakeholders
•Translate business goals into technical plans, milestones and trade-offs, and raise risks early
•Ensure initiatives reach production with measurable, explainable outcomes
•Design AI systems and define reusable architectures, patterns and engineering standards
•Document trade-off decisions across quality, latency, cost, security and vendor dependency
•Solve complex technical problems and unblock teams
•Establish evaluation datasets, regression tracking, quality metrics and acceptance criteria for AI systems
•Ensure systems are tested against realistic cases before and after production release
•Define telemetry for end-to-end cost, latency, quality and outcomes
•Lead reliability, scalability, resilience, observability and incident-learning practices for AI services
•Identify structural improvements from production behavior and drive their completion with owning teams
•Control costs through routing, caching, context management and capacity decisions
•Design permissions, guardrails, audit trails and human-in-the-loop checkpoints for agents accessing internal systems
•Work with Security, Legal, Compliance and IT to build governance requirements into reusable components
•Mentor engineers and tech leads and raise teams' technical standards
•Create reusable playbooks, templates, shared libraries and documentation
•Communicate technical decisions to technical and non-technical stakeholders and align teams on shared standards
•Share knowledge through internal write-ups and tech talks, and occasionally at external meetups and conferences
Requirements
•8+ Years of software engineering experience, including significant experience at senior or Staff-level scope
•2+ Years of hands-on experience building and operating LLM-based systems, ideally in production
•Experience designing agentic or multi-step AI systems involving tool use, orchestration, state, retrieval or external integrations
•Strong foundations in distributed systems and software architecture
•Knowledge of cloud infrastructure, preferably AWS, and secure, cost-conscious service operations
•Experience with observability, testing and evaluation of complex systems
•Track record of technically leading initiatives involving multiple teams from design through production
•Ability to align scope, priorities and outcomes with business stakeholders and engineering peers
•Ability to assess trade-offs, make decisions with incomplete information and remain effective in crises
•Experience defining engineering standards and best practices adopted by teams
•Ability to influence without authority and explain technical decisions to non-specialists clearly and concisely
•Builder mindset, preference for reusable platforms and tools, curiosity, experimentation, disciplined measurement, risk awareness, comfort with ambiguity, ability to structure work and keep stakeholders informed
Nice to have
•Experience with LangChain, LangGraph, Claude Agent SDK or MCP
•Kubernetes and containerized execution environments
•LLM gateways, model routing and cost management
•Machine learning or applied research
•Regulated environments such as payments or financial services
Conditions
•Flexible schedules focused on impact and productivity rather than fixed hours
•Country-specific benefits
•Referral bonus program
•Team members can work while traveling for up to 3 months every year
