Staff Automation Engineer & AI Engineer

About the role

Come Make an Impact on Millions of Brazilians! At RecargaPay, we're on a mission to deliver the best payment experience for Brazilian consumers and small businesses, by building a powerful digital ecosystem where the banked and unbanked connect, and where consumers and merchants have a one-stop shop for all their financial needs. We serve over 10 million users and process more than USD 4 billion annually. We've been profitable since 2022 and operate our own credit business. We are an AI-first, 100% remote team, scaling in the rapidly changing Brazilian financial market. Our goal? Deliver the best payment experience in Brazil for people and small businesses alike. We value autonomy, ownership, and a bias for action. We're looking for people who are curious, hands-on, and driven by impact, who want to solve real problems, work with strong teams, and rethink what's possible. If you're ready to do your best work, at scale, with purpose, this is your place. Responsibilities As a Staff Automation Engineer , you will be the senior technical reference for the automation area, setting the engineering direction for complex automation initiatives. You will define the architectural vision, lead the company's automation strategy, and disseminate healthy development and agentic development practices. You will act as a bridge between technology and business, translating strategic objectives into scalable and secure automation solutions, and developing technical capabilities across the team through mentoring, standards, enablement, and leadership by example. Although this is a technical role, it is expected to remain hands-on, directly contributing to complex implementations, architectural decisions, code reviews, troubleshooting, and production support for business-critical automations. Key Responsibilities Define the automation operating model, including intake process, prioritization criteria, ownership, support model, governance forums, development standards, and lifecycle management. Define prioritization criteria for the automation portfolio based on business impact, operational risk, effort, scalability, maintainability, and ROI. Define observability, auditability, supportability, and incident management standards for business-critical automations. Establish standards for logs, metrics, alerts, execution history, audit trails, runbooks, ownership, and post-incident reviews. Define AI governance and LLMOps practices, including prompt/version management, evaluation datasets, model selection criteria, hallucination mitigation, human-in-the-loop patterns, access control, traceability, and responsible AI usage. Design reusable automation components, templates, connectors, libraries, golden paths, and reference architectures to accelerate delivery and standardize quality. Evaluate, select, and govern automation, RPA, workflow, and AI orchestration tools based on scalability, security, cost, vendor lock-in, maintainability, and enterprise fit. Establish standards for highly validated automation flows, ensuring every process includes automated reconciliation mechanisms and audit trails to maintain data integrity across systems. Define the governance for "Human-in-the-loop" patterns in automated financial and operational workflows to ensure high-trust execution in regulated environments.Embed risk, compliance, privacy, segregation of duties, approval flows, and audit controls into automation design. Define architecture, governance, scalability, monitoring, reusable patterns, and operational standards for n8n or similar workflow automation platforms. Design production-grade AI workflows and agents using tools such as Langflow, LangGraph, CrewAI, Semantic Kernel, or similar, including RAG, tool usage, multi-LLM integration, evaluations, and human-in-the-loop controls. Define contracts, integration patterns, and API governance in the automation context. Govern RPA tools such as UiPath, Blue Prism, Automation Anywhere, or Power Automate, defining when to use RPA versus APIs, workflows, scripts, AI tools, or system integrations. Define when automations should run as scripts, serverless functions, containers, workflows, or platform services. Define and audit development security practices and information management in the team. Define guidelines for the responsible and effective use of Claude Code, Codex, Cursor, GitHub Copilot, or similar AI-assisted engineering tools, promoting code quality, testing, documentation, security, and sustainable engineering practices. Remain hands-on, directly contributing to complex implementations, architectural decisions, code reviews, troubleshooting, and production support for business-critical automations. Mentor and develop technical capabilities across the team through standards, enablement, and leadership by example. Academic background oriented toward computer science, engineering, or software development disciplines. Python with mastery: production-grade code, architectural review, and def