Senior Backend Engineer

Description

The company is a stablecoin-native banking platform for global enterprises, serving thousands of businesses in 35 countries with corporate cards, payments, treasury and spend management on one product.

Annualized volume is above $5B, with payouts to 190 countries and one of the fastest-growing stablecoin payment networks. Customers include BMW, H&M, Lululemon, Burger King, Kavak and XP, and more than 80% use several products.

The company has raised more than $400 million in equity funding from Andreessen Horowitz, Y Combinator, CRV, Coinbase Ventures, GIC, AllianceBernstein, CoinFund and others.

The company works on hard problems on purpose and hires for relentlessness: people who keep pushing when there is no playbook. The learning curve is steep.

The role is a senior backend position on the engineering team, working on the backend for payments, cards, spend management and compliance infrastructure that serves businesses across the Americas and beyond.

This is a backend engineering role at its core. The company wants a strong backend engineer who works well with AI tools, sees where AI can speed up development and product features, and is comfortable putting AI-powered features into production backend systems.

Responsibilities

• Design, build and maintain reliable, scalable backend services that process financial transactions for customers in more than 20 countries.
• Write clean, testable, production-quality code in Go, Python, or Node.js/TypeScript, and take an active part in design and code reviews.
• Build and use RESTful and GraphQL APIs, and design service-to-service communication with gRPC, message queues and event-driven patterns.
• Design and tune relational and non-relational schemas in PostgreSQL, MongoDB and Redis for correctness, speed and scale.
• Own backend features from scoping and technical design through deployment, monitoring and later iterations.
• Apply security practices across distributed services, including authentication, authorization, input validation and data protection.
• Add LLM API calls (such as OpenAI or Anthropic) to backend services for features like spend categorization, document parsing or natural language workflows, keeping them reliable, observable and cost-efficient.
• Build pipelines that check AI output before use, handle fallbacks, and degrade gracefully when AI services are down or return low-confidence results.
• Work with AI and data science teams to expose model outputs through backend APIs, turning experimental work into production systems.
• Use AI coding tools such as GitHub Copilot, Claude or Cursor fluently in your daily work.
• Add structured logging, distributed tracing and metrics so services are fully visible in operation.
• Take part in the on-call rotation, respond to production incidents and contribute to post-incident reviews.
• Help improve CI/CD pipelines, test infrastructure and deployment practices.
• Work with engineering, product, compliance and data teams across time zones and regions, communicating in English and in Spanish or Portuguese when needed.
• Help build a distributed engineering culture through clear documentation, async design reviews and useful pull request feedback.
• Bring a regional view to product and engineering discussions, since LATAM customers have specific needs.

Requirements

• At least 5 years of professional backend engineering experience building and running production systems.
• Professional fluency in English for daily work with global teams, in writing and speaking.
• Strong proficiency in at least one backend language: Go, Python, or Node.js/TypeScript.
• Experience designing and building RESTful APIs, microservices and event-driven backend systems.
• Solid grasp of relational databases, ideally PostgreSQL, including schema design, query optimization and data modeling.
• Experience with cloud infrastructure on AWS, GCP or Azure, containers (Docker, Kubernetes) and CI/CD pipelines.
• Proven record of integrating third-party APIs reliably in production, with error handling, retry logic and observability.
• Experience working on globally distributed teams across time zones and regions.
• Comfortable using AI tools in everyday engineering, including wiring LLM API outputs into backend services and using AI coding assistants well.
• Preferred: experience in fintech, financial services, payments or another regulated industry, with familiarity with ledger systems, payment rails or financial compliance such as KYC/AML and PCI-DSS.
• Preferred: fluency in Spanish or Portuguese for work with LATAM teammates, customers and operational partners.
• Preferred: prior experience at a startup or high-growth scale-up, comfortable building without heavy process.
• Preferred: experience with multi-currency systems or cross-border payment processing.
• Preferred: familiarity with message queues such as Kafka or RabbitMQ and event-driven architecture.
• Preferred: prior work at companies operating across several countries and regulatory environments.

Conditions

Equal opportunity employer.