Devops engineer
Pubblicato il 30-08-2026 - Rapyd in Italia
Rapyd has unified payments, payouts and fintech on one worldwide platform, and we're assembling the world's best team to liberate global commerce. With offices in Tel Aviv, Amsterdam, Singapore, Iceland, London, Dubai, Hong Kong, and the U. S., the opportunities at Rapyd are limitless. We believe in straight talk, quick decisions, strong execution and elegant solutions. Rapyd is where hard work pays off and careers take off. Join us and let's build the future of fintech together.
As a Dev Ops Engineer at Rapyd, you will play a central role in designing, automating, and scaling our global fintech infrastructure. You will work closely with cross-functional engineering teams to maintain high availability, build robust CI/CD pipelines, and codify multi-account cloud environments on AWS.
This is a hands-on position where you will turn complex operational challenges into reliable, automated solutions Our Dev Ops engineers ship with Cursor, Claude, and specialized CLI assistants as first-class tools, handling boilerplate Infrastructure as Code (Ia C) generation, Python automation scripts,
and CI/CD pipeline troubleshooting. People who thrive here design their own AI-assisted workflows to eliminate repetitive toil and move at high speed.
If you've ever felt limited by a team that wasn't automating as fast as you could, this is the environment you've been looking for. Key Responsabilities Automate Infrastructure: Write scalable, maintainable Terraform and Python code to manage cloud resources and operational processes.
Manage Containers: Deploy, scale, and optimize microservices running on Kubernetes (EKS).
Build CI/CD Pipelines: Design and maintain robust continuous integration and deployment pipelines to ensure fast, reliable releases. Cloud & Network Design: Configure multi-account AWS architectures, VPCs, low-level routing, and security controls. Observability & Optimization: Drive system performance tuning, monitoring, and cloud cost optimization using Cloud Watch, Data