Staff Automation Engineer & AI Engineer

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 definition of patterns for the team. Workflow automation platforms: defines architecture, governance, scalability, monitoring, reusable patterns, and operational standards for n8n or similar platforms. AI orchestration platforms: designs 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. APIs: defines contracts, integration patterns, and API governance in the automation context. Advanced AWS: cloud architecture for automations at scale, costs, resilience, and compliance. RPA strategy and governance: governs 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. Container and deployment architecture: understands Docker and Kubernetes-based deployment models and defines when automations should run as scripts, serverless functions, containers, workflows, or platform services. Advanced security: defines and audits development security practices and information management in the team. AI-assisted engineering practices: defines guidelines for the responsible and effective use of Claude Code, Codex, Cursor, GitHub Copilot, or similar tools, promoting code quality, testing, documentation, security, and sustainable engineering practices. FinOps view: considers cost, efficiency, and operational impact in all architectural decisions. Practical experience applying AI frameworks in production projects. Soft Skills Strategic view of automation as a transversal capability of the company. Technical influence on product, operations, and engineering decisions. Executive communication: capable of presenting ROI, risks, and trade-offs to leadership. Building automation and agentic development culture in the team. High capacity for mentorship and people development. Leadership by example: reference in quality, security, and innovation. Oriented toward business outcomes, not just technical delivery. Industry-Specific Knowledge As a Staff Automation Engineer, you bring deep, hands-on familiarity with enterprise platforms, internal operations, and back-office workflows, paired with a strategic understanding of business processes, compliance frameworks, and the drivers of operational efficiency that define these areas. You leverage this expertise to consolidate automation as a transversal capability of the company, accelerating delivery across functions such as Finance, HR, Legal, Compliance, Risk, and Internal Operations. Beyond shaping the technical direction, you act as a key partner to Product Managers, Process Owners, and Business and Operation Leaders, collaborating to define roadmaps, evaluate trade-offs, and guide decisions that balance delivery speed, system reliability, regulatory compliance, and long-term business impact. You translate domain-specific needs into actionable technical direction and drive a culture in which automation outcomes are measured not just by execution, but by their tangible impact on process efficiency, data quality, compliance posture, cost reduction, and internal user experience, often enabled by the strategic use of AI agents, LLM-based workflows, and intelligent automation. Competitive and market-aligned salary. Remote work — wherever you are, you’re part of the team! Home office allowance through a monthly deposit in the RecargaPay app. Health and dental plans with no co-pay. Life insurance. Flexible meal allowance (via Flash). TotalPass membership to take care of your health. Diversity & Inclusion at RecargaPay At RecargaPay, you’ll have the freedom to be who you are because we believe that diverse perspectives and experiences make us more creative and stronger. Here, everyone is welcome to express themselves authentically. We value the richness of each journey and the multiple ways of seeing the world, without distinctions of gender, race, sexual orientation, age, religion, or any other characteristic that makes us unique. About the use of your Data By sharing your resume with us, you authorize the use of your data for analysis during the selection process and possibly for other opportunities within the RecargaPay group. You can request the update or deletion of your information at any time, in accordance with LGPD (General Data Protection Law). Industry-Specific Knowledge It is desirable to have practical familiarity with one or more core financial domains such as lending, payments, credit cards, open finance, fraud prevention, merchant acquiring, or investment services, along with an understanding of their fundamental workflows and business drivers. Experience in how these domains intersect to influence revenue, risk management, and customer satisfaction is highly valued. Ideally, candidates will have applied this knowledge to deliver solutions such as loan-origination engines with real-time decisioning; scalable payment-processing platforms integrated with core banking systems and third-party gateways; secure open-finance interfaces compliant with industry regulations; automated fraud-detection pipelines leveraging behavioral analytics; or financial reporting and reconciliation engines for regulatory compliance. The ability to translate complex compliance mandates (e.g., KYC/AML, PCI-DSS, GDPR) into resilient, high-performance systems without compromising user experience is considered a strong asset.