AI-Driven Telecom Security Engineer

Zealot Labs, Inc.; New York (NY); Presencial; USD 100.000 - 195.000; Jornada completa

Descripción de la vacante

Zealot Labs, Inc. seeks a security-focused engineer to build AI systems that defend carrier networks and exploit research pathways. You will work on core routers, BRAS/BNG, GPON/EPON, and mobile packet cores with C/C++ and Python tooling.

You'll reverse engineer firmware from Nokia, Ericsson, Huawei, ZTE, Calix, and similar vendors, developing scalable AI agents and models that generalize across platforms, in a hands-on early-stage startup environment.

Formación

• Experience in telecom or ISP infrastructure security (core networks, access networks, carrier routing).
• Strong C/C++ and/or Python skills for tooling and exploit development.
• Ability to reverse engineer firmware and management planes on carrier equipment.

Responsabilidades

• Build AI systems that find and exploit vulnerabilities in carrier-grade telecom and ISP infrastructure (routers, BRAS/BNG, GPON/EPON, DSLAM, CMTS, mobile packet core).
• Reverse engineer firmware and management planes on equipment from Nokia, Ericsson, Huawei, ZTE, Calix to train cross-platform models.
• Target subscriber-edge infrastructure (BRAS/BNG, AAA systems, RADIUS/DIAMETER) where auth and policy converge.
• Develop AI-driven tooling to discover attack paths through SS7, GTP, DIAMETER, and carrier routing at scale.
• Turn deep telecom domain knowledge into systems and data for AI agents to operate at backbone level.

Conocimientos

C/C++

Python

Telecom security

Carrier routing

Herramientas

TR-069/CWMP

NETCONF/YANG

RADIUS/DIAMETER AAA

Descripción del empleo

Zealot Labs, Inc. seeks a security-focused engineer to build AI systems that defend carrier networks and exploit research pathways. You will work on core routers, BRAS/BNG, GPON/EPON, and mobile packet cores with C/C++ and Python tooling.

You'll reverse engineer firmware from Nokia, Ericsson, Huawei, ZTE, Calix, and similar vendors, developing scalable AI agents and models that generalize across platforms, in a hands-on early-stage startup environment.