AI Platform Engineer

What You'll Be Doing

• Build and run the internal platform ScaleOps R&D builds on: CI/CD, Kubernetes tooling, developer experience, and infrastructure automation
• Give every engineer a fast, safe path to develop, test, and ship code to production
• Build and connect AI tools for R&D and the company, and bring new tools and best practices from the market into how we build the product
• Build infrastructure for the other R&D teams, from internal agentic platforms to the foundations that LLM-powered automation runs on
• Partner closely with backend, product, and R&D teams, and treat engineers as your customers: measure adoption and time saved
• Identify and eliminate friction in the development lifecycle through automation and self-service tooling

What You'll Bring

• 5+ years of hands-on experience in platform engineering, infrastructure, or AI/ML infrastructure in high-scale environments
• Experience building self-service platforms or tooling that other engineers adopted
• Strong hands-on experience with Kubernetes, cloud (AWS, GCP, or Azure), and infrastructure-as-code
• Strong development skills: you have written production code, ideally Go, such as Kubernetes operators or controllers
• A builder mindset, strong ownership, and curiosity about the AI market and its tooling
• Full professional fluency in Hebrew and English (ב-US: “Full professional fluency in English”)
• (Nice to have) Open-source contributions in the cloud-native space (Karpenter, Cilium, KEDA, Argo, Kueue)
• (Nice to have) Experience with LLM serving, agentic frameworks, or MCP-based tooling
• (Nice to have) Experience with scheduling, node lifecycle, or resource management in Kubernetes