Applied AI Security Engineer: Frontier Threat Detection

swift

Greater London

Vor Ort

GBP 90.000 - 150.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

Swift, the global leader in secure financial messaging, seeks a frontier AI security researcher to run AI/LLM–driven vulnerability discovery against SWIFT codebases and integrate AI-assisted detection into development workflows.

Required are hands-on AI/LLM security experience, strong coding skills across languages, solid knowledge of common vulnerabilities and tooling, and a proven ability to build pipelines and document decisions for peer review.

Qualifikationen

  • Hands-on experience applying AI/LLM models to security testing.
  • Ability to read and reason about large codebases across languages.
  • Understanding of vulnerability classes and analysis tools.
  • Experience building tools and pipelines from scratch.

Aufgaben

  • Run frontier AI models against SWIFT's codebases to find vulnerabilities.
  • Develop the methodology through experimentation.
  • Build an AI-assisted detection pipeline, dedupe findings, route issues to remediation.
  • Run evaluations of frontier models on real detection tasks and decide which to rely on.
  • Integrate AI-assisted detection into SWIFT software development with existing tooling.
  • Identify vulnerability classes unseen by current tooling and build detection approaches.
  • Work within governed access and tooling controls.
  • Document methodology for peer scrutiny.

Kenntnisse

AI/LLM security
Code reading across languages
Application security fundamentals
Scripting & automation
Technical evaluation design
Ambiguity tolerance
Technical communication

Ausbildung

Bachelor's degree in CS/IS or related
Masters degree an asset

Jobbeschreibung

Swift, the global leader in secure financial messaging, seeks a frontier AI security researcher to run AI/LLM–driven vulnerability discovery against SWIFT codebases and integrate AI-assisted detection into development workflows.

Required are hands-on AI/LLM security experience, strong coding skills across languages, solid knowledge of common vulnerabilities and tooling, and a proven ability to build pipelines and document decisions for peer review.

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