Remote AI Security Engineer — Threat Modeling

Bright Vision Technologies; United States; Remote; USD 150,000 - 170,000; Full time

Job summary

Bright Vision Technologies is seeking an Secure AI Systems Engineer to lead the design and implementation of security controls, threat models, and incident response capabilities tailored to AI and ML systems, including LLMs, model APIs, and data pipelines.

The ideal candidate has hands-on experience building defenses for AI-powered applications and the infrastructure that supports them, along with strong security engineering fundamentals and cloud security knowledge.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or 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.

Responsibilities

• Lead design and implementation of security controls for AI/ML systems.
• Develop threat models and incident response capabilities.
• Evaluate security of AI infrastructure, model APIs, and data pipelines.
• Support secure deployment across cloud environments.

Skills

Security engineering

AI/ML systems

LLM internals

Security controls

Threat modeling

Security architecture

Adversarial ML

Python

Systems language

Cloud security

Communication

Education

Bachelor/Master in CS

Job description

Bright Vision Technologies is seeking an Secure AI Systems Engineer to lead the design and implementation of security controls, threat models, and incident response capabilities tailored to AI and ML systems, including LLMs, model APIs, and data pipelines.

The ideal candidate has hands-on experience building defenses for AI-powered applications and the infrastructure that supports them, along with strong security engineering fundamentals and cloud security knowledge.