Founding Engineer

An elite, high-profile Cybersecurity & AI-Native startup that has recently emerged backed by a massive, top-tier funding round from world-renowned cyber venture funds.

Operating currently in Stealth Mode, the company is engineering a revolutionary, AI-native management and automated investigation platform that completely replaces fragmented, legacy enterprise ticketing systems (such as Jira) within security environments.

Operating as a highly selective, foundational core group, this is an exceptional, high-equity opportunity to join the founding engineering team as they build a market-disrupting infrastructure from scratch.

The company's corporate headquarters is located in a prime Tel Aviv location (exceptionally accessible, situated within immediate walking distance of major train and light rail lines) and operates on an intensive, high-velocity 5 days in-office model.

Position Overview-

Founding Core Full-Stack Engineer joining an elite R&D squad of 7 developers to design, architect, and implement the platform’s foundational engine completely from scratch.

Writing performance-critical, data-intensive backend architectures primarily in Python (~80% of the stack) deployed over robust AWS cloud infrastructures.

Developing slick, intuitive, and highly responsive user interfaces utilizing React to visualize complex attack paths and forensic timelines.

Working in direct collaboration with the CTO to integrate advanced LLMs and cognitive automation agents natively into the core product architecture.

Requirements-

5 years of proven professional software engineering experience in Python, Go, or C++ within product-centric organizations (Mandatory).

Strong, hands-on production experience building user interfaces using React (Mandatory).

Solid technical proficiency architecting and deploying systems over public cloud environments, specifically AWS (Mandatory).

Deep, practical development experience operating within Linux environments (Mandatory).

Practical understanding of building event-driven architectures, distributed systems, or integrating foundational LLM/GenAI components is highly advantageous.

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