Senior Software Engineer (AI)

Location: Remote, Latin America

Company

hirify.global is working with a fast-growing, Series A-backed AI company delivering agentic AI solutions to banks and credit unions. The platform serves more than 100 financial institutions and over 10 million end users.

What you will do

• Design, develop, and maintain scalable backend services for AI-powered financial products.
• Make technical decisions across architecture, APIs, data models, performance, security, and reliability.
• Build backend applications with TypeScript and Python, contributing to frontend functionality with JavaScript when needed.
• Integrate LLMs and agentic AI capabilities into production applications.
• Design and operate distributed, cloud-native systems with strong observability and operational excellence.
• Define engineering practices for code quality, testing, deployment, and incident response while collaborating with product, design, data, and engineering leadership.

Requirements

• 5+ years of professional software engineering experience building production-grade applications.
• Strong proficiency in TypeScript and/or Python.
• Experience designing scalable backend systems, APIs, and distributed architectures.
• Strong knowledge of cloud platforms such as AWS or GCP.
• Hands-on experience integrating LLMs into production applications and using prompt engineering to solve business problems.
• Understanding of software architecture, scalability, performance optimization, reliability, and security, plus a bachelor's degree in Computer Science or a related discipline.

Nice to have

• Experience with conversational AI, agentic AI, NLP, or dialogue systems.
• Fintech, banking, or regulated-industry experience.
• Startup experience building products from early stages through scale.
• Experience with observability, CI/CD, Kubernetes, Docker, and modern DevOps practices.
• Familiarity with AI developer tools such as Cursor or Claude Code.

Culture & Benefits

• Hands-on engineering ownership across architecture, implementation, and delivery.
• Direct collaboration with the VP of Engineering, CTO, and CEO.
• Opportunity to build production AI systems used by millions of banking customers.
• Work on practical LLM and agentic AI applications in intelligent financial services.