Dream is a pioneering AI cybersecurity company delivering revolutionary defense through artificial intelligence. Our proprietary AI platform creates a unified security system safeguarding assets against existing and emerging generative cyber threats. Dream's advanced AI automates discovery, calculates risks, performs real-time threat detection, and plans an automated response. With a core focus on the ""unknowns,"" our AI transforms data into clear threat narratives and actionable defense strategies.

Dream's AI cybersecurity platform represents a paradigm shift in cyber defense, employing a novel, multi-layered approach across all organizational networks in real-time. At the core of our solution is Dream's proprietary Cyber Language Model, a groundbreaking innovation that provides real-time, contextualized intelligence for comprehensive, actionable insights into any cyber-related query or threat scenario.

We’re building the next generation of autonomous cybersecurity — technology that thinks like an attacker to continuously expose real-world security gaps before adversaries do.

As a Senior Attack Simulation Engineer, you’ll design and build the engines, data models, and intelligent agents that emulate advanced threat actors across massive enterprise networks. You’ll blend exceptional software engineering skills with deep security insight to create systems that mirror human adversaries — finding weaknesses before they’re exploited.

Responsibilities:

• Model and simulate attack paths across complex enterprise ecosystems — identity, endpoint, network, and cloud.
• Design AI-driven agents that perform adversarial behaviors like lateral movement, privilege escalation, and persistence.
• Build and optimize core simulation and orchestration components in Go (primary language), integrating with in-house AI models and security telemetry.
• Collaborate with red teamers, researchers, and data scientists to translate cutting-edge threat intelligence into executable simulations.
• Analyze large-scale datasets from simulations and live environments to refine attack-path prediction and prioritization.
• Drive architecture, scalability, and performance improvements for distributed simulation systems.
  
  

Skills:

• 5+ years of hands-on software engineering experience in a modern language (Go preferred; Python, Node.js, or C++ also great).
• Strong cybersecurity background — experience as a red teamer, penetration tester, or security researcher.
• Deep understanding of attacker TTPs, lateral movement, privilege escalation, credential abuse, and network exploitation.
• Familiarity with enterprise security environments (Active Directory, cloud infrastructure, EDR/XDR, network segmentation).
  
  

Advantages:

• Experience building AI/ML-driven systems or agent-based simulations.
• Knowledge of graph modelling or graph databases (e.g., Neo4j) for attack-path representation.