Secure AI Systems Engineer

Bright Vision Technologies•Wildwood, MO
•$150,000 - $170,000•Remote

About The Position

Bright Vision Technologies is seeking a Secure AI Systems Engineer to lead the design and implementation of security controls, threat models, and incident response capabilities tailored to AI and machine learning systems. The role addresses security challenges involving LLMs, model APIs, training data pipelines, and AI-powered applications, including prompt injection, model abuse, data exfiltration, and supply chain risks. The ideal candidate combines strong security engineering fundamentals with a practical understanding of modern AI systems and hands-on experience designing defenses for AI-powered applications and supporting infrastructure. The position is 100% remote in the United States, full-time, and direct W2. The annual salary range is $150,000–$170,000. Bright Vision Technologies is unable to sponsor new H-1B visa petitions for this position; U.S. citizens, Green Card holders, EAD holders, and H-1B transfer candidates are encouraged to apply.

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 tailored to AI and machine learning systems.
  • Develop threat models and incident response capabilities for AI systems.
  • Design defenses for AI-powered applications and the AI infrastructure that supports them.
  • Address risks including prompt injection, model abuse, data exfiltration, and supply chain threats.
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