AI Security Engineer

Bright Vision TechnologiesDes Plaines, IL
$80,000 - $105,000Remote

About The Position

We are seeking an AI Security Engineer to lead the design and implementation of security controls, threat models, and incident response capabilities specifically tailored to AI and machine learning systems. The role addresses the unique security challenges posed by LLMs, model APIs, training data pipelines, and AI-powered applications, including prompt injection, model abuse, data exfiltration, and supply chain risks. The ideal candidate has strong security engineering fundamentals and a deep understanding of how modern AI systems work in practice, with hands-on experience designing defenses for both AI-powered applications and the AI infrastructure that supports them.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or a related discipline.
  • Six or more years of security engineering experience, including significant work on AI or ML systems.
  • Strong understanding of LLM internals, modern AI architectures, and common failure modes.
  • Hands-on experience designing security controls for AI-powered applications.
  • Deep knowledge of application security, identity, and cryptography fundamentals.
  • Experience with threat modeling and security architecture review processes.
  • Familiarity with adversarial ML, prompt injection, and model abuse research.
  • Proficiency in Python and at least one systems language.
  • Strong understanding of cloud security and modern infrastructure controls.
  • Excellent written and verbal communication skills.

Nice To Haves

  • Publications, talks, or CTF participation in AI security topics.
  • Experience with red-teaming LLM-based products.
  • Familiarity with privacy-preserving ML techniques such as differential privacy.
  • Exposure to regulated industries with strict data handling requirements.
  • Open-source contributions to AI security tooling.

Responsibilities

  • Lead the design and implementation of security controls for AI and machine learning systems.
  • Develop threat models for AI systems.
  • Establish incident response capabilities for AI systems.
  • Address security challenges related to LLMs, model APIs, training data pipelines, and AI-powered applications.
  • Design defenses against prompt injection, model abuse, data exfiltration, and supply chain risks.
  • Design security controls for AI-powered applications and their supporting infrastructure.
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