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Offensive Security Analyst (Structured / Non-Exploit)

Offre en anglais

Analyze attack paths and adversary strategies to generate and validate adversarial reasoning data for AI training. Identify defensive gaps and misconfigurations to help AI systems better reason about cybersecurity threats.

  • Télétravail
  • Vancouver, British Columbia, Canada
  • Publié 3 août 2026
  • Postuler avant le 2 sept. 2026
  • 1 poste

Résumé du poste

Offensive Security Analyst (Structured / Non-Exploit) — AI Training About The Role What if your deep understanding of how attackers think could directly shape how AI reasons about cybersecurity threats? We're looking for offensive security professionals to analyze real-world attack paths, adversary behavior, and defensive gaps — helping train and evaluate the next generation of AI systems. This role is about structured adversarial reasoning, not exploit development. No CVEs, no shellcode — just sharp, methodical thinking about how threats move through real environments and where defenses break down. This is a fully remote, flexible contract role built for experienced security professionals who want meaningful, high-impact work on their own schedule. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Analyze attack paths, kill chains, and adversary strategies across realistic, real-world system scenarios Identify and classify weaknesses, misconfigurations, and defensive gaps that attackers would exploit Review red-team-style scenarios and intrusion narratives for technical accuracy and depth Generate, label, and validate adversarial reasoning data used to train and evaluate AI systems Articulate complex attack chains, business impact, and risk tradeoffs in clear, structured language Who You Are 2+ years of hands-on experience in pentesting, red teaming, or a blue-team role with strong offensive knowledge You understand how real attacks unfold in production environments — not just in theory You can walk through an attack chain from initial access to impact and explain every step clearly Detail-oriented and methodical — you spot what others miss Comfortable working independently and asynchronously without close supervision Nice to Have Familiarity with frameworks like MITRE ATT&CK, Cyber Kill Chain, or STRIDE Experience writing threat models, purple team reports, or adversary simulation documentation Background in cloud security, Active Directory attacks, or network intrusion scenarios Prior exposure to AI tools, data labeling, or security research writing Why Join Us Work directly on frontier AI systems alongside leading research labs Fully remote and flexible — work when and where it suits you Freelance autonomy with the structure of meaningful, task-based work Apply your offensive security expertise to a domain where it creates lasting, large-scale impact Potential for ongoing work and contract extension as new projects launch

Ce que vous ferez

Analyze attack paths and adversary strategies to generate and validate adversarial reasoning data for AI training. Identify defensive gaps and misconfigurations to help AI systems better reason about cybersecurity threats.

Exigences

Requires 2+ years of hands-on experience in pentesting, red teaming, or offensive-focused blue teaming. Candidates must be able to clearly articulate complex attack chains and work independently in an asynchronous environment.

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

  • Pentesting
  • Red Teaming
  • Adversarial Reasoning
  • Attack Path Analysis
  • Threat Modeling
  • Cloud Security
  • Active Directory Attacks
  • Network Intrusion
  • MITRE ATT&CK
  • Cyber Kill Chain
  • STRIDE
  • Data Labeling

Domaines d’emploi

  • Security & Safety
  • Technology
  • Software
  • Data & Analytics
  • Consulting

Renseignements supplémentaires

Expérience minimale
2+ ans
Postuler avant le
2 sept. 2026
Langue de l’offre
anglais
Heures de travail
40 heures par semaine
Exigences de lieu
Country, Vancouver, British Columbia, Canada
Niveau d’expérience
Entry level