Software Development Engineer

Location Details: Colombia, remote

At GoDaddy, the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) , and some work entirely remotely.​

This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings.  

Join Our Team

Join our Growth team, where you'll build intelligent agents that serve hundreds to thousands of customers in production. We're at the forefront of applying AI to solve real business problems at scale. You'll architect, deploy, and operate AI-powered systems in live environments, tackling challenges in reliability, scalability, and performance as we grow our AI footprint across GoDaddy.

What you'll get to do...

• Design, develop, and deploy production-ready AI agents and services using Node.js, LLMs (OpenAI, Anthropic, or similar), and modern cloud technologies.
• Drive technical design and architecture decisions for scalable, reliable, and maintainable AI-powered systems serving thousands of customers.
• Own end-to-end delivery of complex engineering initiatives, including backend services, API development, AI orchestration workflows, and production operations.
• Collaborate closely with Product, Design, Business Analytics, and Engineering teams to influence technical direction and deliver impactful customer experiences.
• Mentor engineers through code reviews, technical guidance, and knowledge sharing while helping elevate engineering standards and operational excellence.

Your experience should include...

• 6+ years of professional software engineering experience building and operating scalable distributed systems and full-stack applications.
• Strong expertise in backend development using Node.js, Python, Go, or similar technologies, with a deep understanding of software design principles.
• Experience leading technical initiatives from architecture and design through deployment and production support.
• Hands-on experience with cloud platforms such as AWS or Azure, including infrastructure design, monitoring, reliability, and scale.
• Strong knowledge of distributed systems, microservices, API design, event-driven architectures, databases, CI/CD pipelines, and containerized environments.

You might also have...

• Experience building and operating AI-powered applications using LLMs, AI frameworks, and production-grade AI infrastructure.