Armis Security

StaffAIPlatformEngineer

$520–780k ~AI est. Tel Aviv-Yafo, Tel Aviv District, Israel
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Staff AI Platform Engineer at Armis Security”

Full Job Description

Armis, the cyber exposure management & security company, protects the entire attack surface and manages an organization’s cyber risk exposure in real time. In a rapidly evolving, perimeter-less world, Armis ensures that organizations continuously see, protect and manage all critical assets - from the ground to the cloud. Armis secures Fortune 100, 200 and 500 companies as well as national governments, state and local entities to help keep critical infrastructure, economies and society stay safe and secure 24/7. Armis is a privately held company headquartered in California. We are looking for a Staff AI Platform Engineer to join the Development Platform team, which is responsible for accelerating Armis R&D velocity and elevating product quality. We need a pragmatic systems thinker who is deeply passionate about Developer Tools (DevTools) and the future of generative AI. You can architect a distributed LLM workflow in the morning, and influence engineering behavior across the entire org in the afternoon. In this role, you will enable 200+ engineers to safely and reliably leverage agentic AI. What You'll Do Scale Quality, Not Just Code Volume: Solve the hard problem of AI-driven quality by building rigorous measurement frameworks, ensuring that an AI-accelerated org delivers better software, not just more software. Establish AI Governance & Security: Architect guardrails around LLM usage, data privacy, and cost management, ensuring 200+ engineers can innovate rapidly without compromising compliance or security. Optimize the SDLC: Embed autonomous workflows, coding agents, and tool/context design directly into the developer lifecycle to supercharge R&D velocity. Drive Org-Wide Adoption: Act as a force multiplier, leading the organizational rollout of AI developer tooling and setting production best practices across teams. Build Agentic Infrastructure: Design and deploy production-grade multi-agent systems, tackling complex challenges like parallel session isolation, sub

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