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AI Security Engineer / Offensive Security Engineer - Technology
🏢 Truelogic · LatAm · Remoto · publicado 23/09/2026
ABOUT TRUELOGIC
At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.
Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.
By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.
OUR CLIENT
A prominent executive networking organization focused on driving business transformation through high-level strategic discourse.
JOB SUMMARY
Our client is looking for a highly hands-on security engineer to continuously attack, test, and strengthen their AI product and infrastructure. This person should think like a white-hat hacker: spend meaningful time trying to break the system, identify vulnerabilities across agents, APIs, identity, memory, permissions, data flows, and infrastructure, then work directly with engineering to understand, prioritize, and fix what they find.
The candidate should have a strong grounding in modern application and cloud security best practices without feeling the need to reinvent the wheel, and be comfortable using automation and AI agents to accelerate security testing, vulnerability discovery, triage, and remediation. Day to day, this could mean orchestrating agents to probe the system, investigating suspicious behavior or failure modes, reproducing exploits, hardening production systems, and gradually building an iterative d
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