עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!

במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.

מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.

חברה בתחום הייטק / חומרה / תוכנה / סייבר

הוד השרון

חברה בתחום הייטק / חומרה / תוכנה / סייבר

הוד השרון
מלאה
25,000-35,000 ₪ (הערכה מבוססת AI)
הערכה מבוססת AI ולא שכר של המעסיק

We're looking for a hands-on DevOps engineer to design, automate, and operate the environments our platform runs in- public cloud alongside on-premises, including restricted and air-gapped customer sites, and to build them the way infrastructure gets built in 2026: as code, with AI agents doing much of the heavy lifting and your judgment deciding what actually ships.
Two things sit on your plate. The first is our R&D team: the pipelines, paved roads, and self-service tooling that let engineers ship several times a day without asking permission or holding their breath- increasingly built and maintained alongside AI agents rather than by hand. The second is where our software actually lands: customer environments that are rarely identical, often heavily locked down, and occasionally have no route to the internet at all. Making a modern, AI-powered platform run reliably inside those constraints is the genuinely interesting part of this job.

Requirements:
Experience: 5+ years in DevOps, Platform Engineering, or SRE, including ownership of production systems.
Debugging: Strong, systematic troubleshooting under production pressure - across Linux, networking, and Kubernetes.
Kubernetes: Real experience in both development and production environments (OpenShift an advantage).
CI/CD: Hands-on pipeline authoring (Jenkins an advantage - it's a meaningful part of our current stack).
Infrastructure as Code: IaC pipelines in practice (Terraform an advantage).
Cloud: A major cloud provider (Azure a plus).
Delivery tooling: Argo, Helm, Helmfile, or equivalent declarative deployment tooling.
Linux and scripting: Proficient in Linux, with Python or Bash.
Observability: Prometheus, Grafana, ELK, or similar.
AI-assisted workflow: Comfortable working with AI coding agents day to day- and clear-eyed about where they need supervision.
FinOps: Practical experience keeping cloud spend deliberate.
Nice to Have:
Experience running AI/ML or inference workloads (GPU scheduling, vLLM, KServe, Ray, vector databases).
Genuine appetite for new technology and continuous learning.
Strong judgment about production risk- you know which changes deserve caution.
Good with people. You'll work across R&D, support, and occasionally customer-side engineers.

This position is open to all candidates.