Security Software Engineer

Emploi pas sur LinkedIn

🕒 il y a 2 mois

🇺🇸 États-Unis – Télétravail

💵 $170 000 - $210 000 / an

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🧑‍💻 Développeur Full-Stack

👻 Score fantôme 3%

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🗣️🇺🇸🇬🇧 Anglais requis

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RunSybil

11 - 50 employés

Fondée en 2023

🔒 Cybersecurity

🤖 Intelligence artificielle

☁️ SaaS

Cybersecurity • Artificial Intelligence • SaaS

RunSybil est une plateforme de sécurité offensive alimentée par l'IA qui teste en continu les applications et l'infrastructure pour détecter les vulnérabilités exploitables en raisonnant sur les systèmes de la même manière qu'un chercheur humain d'élite. Elle fonctionne à travers toute la pile à chaque déploiement. L'entreprise met l'accent sur des tests offensifs automatisés et continus pour trouver des problèmes exploitables dans le monde réel; les documents publics signalent une levée de fonds de 40 millions de dollars dirigée par Khosla Ventures.

Description

• Research and develop offensive agentic capabilities that become core Sybil features • Hunt for real vulnerabilities across a range of target environments and translate what you find into repeatable, automated techniques • Build and ship end-to-end customer-facing features: from research spike to production deployment • Design and implement LLM-powered tooling that extends Sybil's reach and depth across attack surfaces • Identify gaps in our offensive coverage and propose technical initiatives to close them, without waiting to be asked • Contribute to technical design discussions, review your teammates' work, and hold a high bar for what we ship • Operate with ownership: you define the problem, build the solution, and see it through

🎯 Exigences

• 4 or more years of software engineering experience, with meaningful time in offensive security contexts • Hands-on experience finding vulnerabilities across a variety of targets, whether through red teaming, bug bounty, CTF, or production pentesting • Strong Python fundamentals: you have designed, deployed, and maintained backend systems in production • Comfort with modern JavaScript and React; you can own a feature across the full stack • Experience building with LLMs or generative AI tools, including prompt engineering and integrating model outputs into real workflows • A builder's instinct: you default to figuring things out, not waiting for direction • Familiarity with DevOps and infrastructure concepts; you can own your own deployment pipeline • Strong written communication; you can explain a vulnerability, a design decision, or a tradeoff clearly.

🏖️ Avantages

• meaningful equity

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