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AI Engineer

Zealotמחוז תל אביב, ישראללא צויןFull-timeדרגה: לא צוין

פורסם אתמול · 27 מועמדים

שכר לא צוין במשרה זו

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תובנת Willbi
חובה
  • Experience shipping AI-powered software, such as agents, LLM integrations, inference systems, or AI evaluation infrastructure, beyond a standalone demo
  • End-to-end ownership of production software, from scoping and implementation to deployment, debugging, and iteration
  • Strong engineering fundamentals and ability to investigate failures beneath framework abstractions
  • Practical judgment about speed, reliability, maintainability, and cost tradeoffs
  • High agency, clear prioritization, and concise communication
יתרון
  • Experience building at a pre-seed through Series B startup, or comparable founder/early-engineer ownership
  • Depth in backend, distributed systems, infrastructure, developer tooling, or low-level systems
  • Substantial independent projects or open-source work

חולץ מתיאור המשרה · מתעדכן אוטומטית

תיאור המשרה המלא

המשרה המקורית · נשמר לעיון

Zealot (zealotlabs.com) builds AI systems that find zero-days, emulate target devices, and develop working exploits for U.S. defense and intelligence customers. We are backed by tier-1 U.S. venture firms and industry leaders, with a team that includes alumni of Anthropic, xAI, NSA, USCYBERCOM and Anduril.

You will join a small engineering team where your work shapes the core product, architecture, and technical priorities.

The opportunity

Build the software that makes autonomous AI agents useful and reliable in real cybersecurity environments. The challenge goes beyond connecting a model to an API: agents must operate across tools and target environments, recover from failures, and produce results we can evaluate and trust.

This is a hands-on software engineering role focused on production AI systems, not a research-only or traditional machine-learning role. You will work closely with founders, AI researchers, and security specialists, taking ambiguous problems from first prototype through deployment and operation.

What you will build

• Agent execution systems and tool integrations that connect AI capabilities to cybersecurity workflows and target environments.

• Evaluation and observability infrastructure to measure agent behavior, investigate failures, and turn findings into better systems.

• Backend services, APIs, data pipelines, and internal tooling that support the product as usage and complexity grow.

• Reliable autonomous workflows: debug across the stack and improve reliability, latency, and cost.

• Stage-appropriate architecture: decide when to prototype, when to harden, and what to defer, then own the consequences in production.

What you bring

• Hands-on cybersecurity experience and the ability to explain the systems, problems, and technical decisions you personally worked on.

• Experience shipping AI-powered software, such as agents, LLM integrations, inference systems, or AI evaluation infrastructure, beyond a standalone demo.

• End-to-end ownership of production software, from scoping and implementation to deployment, debugging, and iteration.

• Strong engineering fundamentals and a willingness to investigate failures beneath framework abstractions.

• Practical judgment about speed, reliability, maintainability, and cost, backed by tradeoffs you have implemented and evaluated.

• High agency, clear prioritization, and concise communication. You spot what needs doing, move it forward, and update your view when evidence changes.

Especially useful experience

• Building at a pre-seed through Series B startup, or comparable founder, early-engineer, or resource-constrained ownership.

• Depth in backend, distributed systems, infrastructure, developer tooling, or low-level systems, alongside breadth across the stack.

• Substantial independent projects or open-source work that demonstrate technical curiosity and initiative.

How we work and why join

This is an on-site role in Tel Aviv on a lean, founder-close team. We move quickly, debate ideas directly, and value outcomes over titles or territory. Occasional deadline-driven pushes are part of the work.

You will own meaningful parts of the core product, work across AI and security disciplines, and help define how the engineering organization scales. The work is technically demanding, with direct consequences for defense and intelligence customers and room for your scope to grow with the company.

אודות Zealot
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שאלות על המשרה

  • המשרה לא ציינה שכר. אנחנו מציגים שכר רק כשהמעסיק מפרסם אותו.
דומות וקשורות
Zealot
פורסם אתמול · 27 מועמדים
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