ScaleOps

Kubernetes optimization platform for cost reduction

AI Platform Engineer

Platform EngineeringConfirmed live in the last 24 hours

Full-timeTel Aviv-Yafo, IsraelNo salary listedIn-person

About the Job

Requirements

At least 5 years of hands-on experience in platform engineering, infrastructure, or artificial intelligence/machine-learning infrastructure in high-scale environments.
Experience building self-service platforms or tooling adopted by other engineers.
Strong hands-on experience with Kubernetes, cloud platforms such as AWS, GCP, or Azure, and infrastructure as code.
Strong development skills, including production coding; Go is preferred, with examples such as Kubernetes operators or controllers.
Full professional fluency in Hebrew and English.

Responsibilities

Build and operate the internal platform used by ScaleOps R&D, including continuous integration and continuous delivery, Kubernetes tooling, developer experience, and infrastructure automation.
Provide engineers with 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 relevant market tools and best practices into product development.
Build infrastructure for other R&D teams, including internal agentic platforms and foundations for LLM-powered automation.
Partner with backend, product, and R&D teams; measure engineer adoption and time saved.
Identify and eliminate development-lifecycle friction through automation and self-service tooling.

Desired Qualifications

Open-source contributions in the cloud-native space, including Karpenter, Cilium, KEDA, Argo, or Kueue.
Experience with LLM serving, agentic frameworks, or MCP-based tooling.
Experience with scheduling, node lifecycle, or resource management in Kubernetes.

ScaleOps is redefining autonomous cloud and AI infrastructure. We're on a mission to free DevOps and platform engineers from manual resource management so they can focus on innovation, not tuning resources. The results: maximized performance and a reduction of cloud costs by up to 80%.

As the category leader in Autonomous Cloud and AI Infrastructure Resource Management, we're trusted by leading enterprises including Adobe, Wiz, Epic Games, Northwestern Mutual, Coinbase, DocuSign, and Fortune 100 companies to autonomously manage their most critical production environments.

Backed by Insight Partners, Lightspeed Venture Partners, and other leading VCs with over $210M in funding, ScaleOps is the leading player in a massive and growing market. We are building the autonomous infrastructure management platform that will power the next decade of enterprise compute.

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

About the Company

ScaleOps

Kubernetes optimization platform for cost reduction

ScaleOps provides a cloud cost-optimization platform for Kubernetes environments as a SaaS. It automatically manages container resources by rightsizing CPU and memory in real time based on application demand, eliminating manual tuning. It also offers Smart Pod Placement to consolidate pods across nodes when possible, reducing underutilized capacity and lowering infrastructure costs. This combination helps clients improve workload capacity and performance while cutting cloud spend, with case studies reporting up to 50% savings. The platform differentiates itself by end-to-end automated resource management and intelligent placement within Kubernetes, targeting enterprises that run cloud-native applications. ScaleOps’ goal is to help organizations run Kubernetes more efficiently and cost-effectively through subscription-based access to its optimization engine.

Company size: 51-200
Company stage: Series C
Total funding: $209.5M
Headquarters: Tel Aviv-Yafo, Israel
Founded: 2022

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