AI Infrastructure Engineer

Paragon is on a mission to transform the world of cyber intelligence. Based in Tel Aviv, our innovative team is made up of top-tier talent who are passionate about making an impact. At Paragon, you’ll have the freedom to think boldly, collaborate with purpose, and grow alongside a team united by a shared mission; striving for excellence, and always looking out for one another. We are looking for an experienced AI Infrastructure Engineer to join our highly technical R&D organization (~300 engineers). This role focuses on building and operating the infrastructure, tooling, and platforms that enable AI development, rather than developing models themselves. You will work at the intersection of DevOps, backend engineering, and AI systems, supporting advanced teams in a secure, on-premises environment. Responsibilities Design, build, and maintain AI infrastructure and platforms within our R&D environment Develop and operate training and inference environments (GPU clusters, schedulers, containers) Build internal tools and services to support model lifecycle management (versioning, deployment, monitoring) Collaborate closely with AI researchers and developers to optimize workflows and system performance Work with DevOps teams on CI/CD pipelines, automation, and infrastructure-as-code Ensure reliability, reproducibility, and observability of AI systems Troubleshoot complex issues across infrastructure, code, and runtime environments Contribute to architecture decisions in a fully on-prem, secure environment Requirements 4+ years of experience in infrastructure engineering / DevOps / backend systems Strong experience with Linux systems and networking Hands-on experience with containerization and orchestration (Docker, Kubernetes) Experience building and maintaining CI/CD pipelines Strong coding skills (Python, Go, or similar) Experience working closely with software engineers in production environments Solid understanding of distributed systems and system design Ability to operate in a highly technical, fast-paced R&D environment