Security Software Engineer

Vaga não está no LinkedIn

🕒 Julho 28

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $170.000 - $210.000 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

👻 Score fantasma 8%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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RunSybil

11 - 50 funcionários

Fundada em 2023

🔒 Cibersegurança

🤖 Inteligência Artificial

☁️ SaaS

Cybersecurity • Artificial Intelligence • SaaS

RunSybil é uma plataforma de segurança ofensiva movida por IA que testa continuamente aplicações e infraestrutura em busca de vulnerabilidades exploráveis, analisando sistemas da mesma forma que um pesquisador humano de elite faria, operando através de toda a pilha a cada implantação. A empresa enfatiza testes ofensivos automatizados e contínuos para encontrar problemas exploráveis no mundo real; materiais públicos mencionam uma captação de $40 milhões liderada pela Khosla Ventures.

Descrição

• 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

🎯 Requisitos

• 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.

🏖️ Benefícios

• meaningful equity

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