SRE Engineer

Intro

• At JFrog, we’re reinventing DevOps to help the world’s greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if you’re willing to do more, your career can take off. And since software plays a central role in everyone’s lives, you’ll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust JFrog to manage, accelerate, and secure their software delivery from code to production -- a concept we call “liquid software.” Wouldn't it be amazing if you could join us on our journey?
• We are looking for a Site Reliability Engineer to join our SaaS Production team and help us ensure high availability, performance, and reliability across our global cloud environments.
• Support the operation and reliability of JFrog’s large-scale, multi-cloud, Kubernetes-based SaaS environments
• Troubleshoot complex production issues across distributed systems and work closely with Engineering and Cloud teams to resolve them
• Contribute to improving system reliability, performance, scalability, and observability
• Apply SRE best practices, including incident response, service monitoring, capacity considerations, and continuous reliability improvements
• Participate in on-call rotations and take part in incident investigations and postmortems
• Build and enhance automation tools (primarily in Python or Go) to reduce operational toil and improve efficiency
• Assist in improving CI/CD workflows and deployment safety
• Design and develop AI-based tools and automation to improve operational efficiency and productivity for JFrog’s internal engineering and SaaS teams
• Support resilience initiatives, including disaster recovery validation and service readiness improvements
• Continuously learn and explore new technologies that improve operational excellence
• 1-3 years of experience in SRE, DevOps, Production Engineering, or a similar role in a production environment
• Hands-on experience operating Kubernetes-based containerized workloads in production
• Experience with at least one public cloud provider (AWS, GCP, or Azure)
• Strong troubleshooting and analytical skills with the ability to debug production issues methodically