Offensive Security Engineer

Job not on LinkedIn

🕒 February 27

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👮‍♂️ Cybersecurity / Security Engineer

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Logo of Wraithwatch

Wraithwatch

11 - 50 employees

Founded 2023

🎖️ Defense

💼 Consulting

🏭 Manufacturing

💰 $8M Seed Round - Wraithwatch on 2023-10

Defense • Consulting • Manufacturing

Wraithwatch is a weapons-grade cyber defense company that deploys autonomous offense/defense swarms to map networks, hunt threats, and generate machine-speed defenses for the United States and its allies. Their platform performs agentic threat hunting across SIEM indexes, context-aware attack surface analysis against a digital twin, and automated control-plan generation and execution to harden environments and respond to incidents. Wraithwatch targets critical institutions including federal government, aerospace & defense, nuclear and advanced manufacturing, and emphasizes production-safe analysis and rapid, automated remediation.

📋 Description

• Continuously harden Wraithwatch (the company and product) against advanced threats. • Teach the system your expert attack tradecraft and have it evolve to execute it on its own. • Build and ship things on the daily with the core product engineers.

🎯 Requirements

• 5+ years professional experience conducting complex penetration testing assessments in commercial or government environments. • Deep, hands-on understanding of the current landscape of offensive cyber tradecraft (in memory, fileless attacks, beacon object files, malleable C2, modern initial access vectors, emerging EDR bypasses, etc). • Experience implementing or assisting with the implementation of enterprise / corporate security controls such as anti-malware policies, identity and access controls, detection engineering, device management, or similar. • Interest in adapting AI to red teaming / penetration testing use cases. This is a hard requirement. • Interest in modern machine learning or artificial intelligence capabilities, especially emerging subsets of Generative AI such as agentic behavior, tool calling, knowledge graph integration, retrieval augmented generation, etc. • Ability to deal with ambiguity and learn new technologies quickly. • Willingness to work extended hours and weekends as needed.

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