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 go