Senior Software Engineer (Fintech)

TL;DR

Senior Software Engineer (Fintech): Design, build, and scale backend systems powering spend controls, approval workflows, and card transactions at massive scale with an accent on integration with AI platform, financial infrastructure, and partner ecosystems. Focus on owning complex projects end-to-end from architecture to deployment, ensuring reliability, scalability, performance, accuracy, and resilience.

Location: Remote; Argentina

Company

hirify.global builds smart infrastructure for finance teams, embedded in business transaction flows to automate payments, flag risks, categorize spend, and close books for over 50,000 companies handling $100B+ annualized spend.

What you will do

• Design, build, and scale backend systems for spend controls, approval workflows, and card transactions
• Collaborate with product, design, and data teams to deliver intelligent experiences for finance teams
• Integrate with internal AI platform for automating spend policy enforcement and anomaly detection
• Own end-to-end projects from architecture to deployment and observability
• Partner with Product Platform and Integrations teams for reliability and data consistency
• Improve transaction and policy infrastructure for performance, accuracy, and resilience

Requirements

• 6+ years of software engineering experience (backend or fullstack with backend focus)
• Strong fundamentals in backend systems and API design — experience with Python, Go, or TypeScript
• Familiarity with PostgreSQL, AWS, and modern observability tooling
• Product sense to balance technical quality with speed and user value
• Collaborative communicator thriving in high-ownership environments

Nice to have

• Fintech or payments experience (cards, reconciliation, transaction processing)
• Exposure to AI- or rule-based automation systems
• Experience integrating with ERP or accounting systems
• Familiarity with security, risk, or compliance-driven domains
• Experience building reliable distributed systems processing large volumes of financial data