AI Security & Governance Engineer (Remote)

Bright Vision Technologies; Sterling (VA); On-site; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Governance Engineer to lead security design across AI systems, models, and data pipelines. You will implement controls, perform threat modeling, and shape incident response capabilities tailored to LLMs and AI-powered applications.

The role requires deep security engineering fundamentals, hands-on experience securing AI infrastructures, and strong communication skills to collaborate with product and engineering teams.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or a related discipline.
• Six or more years of security engineering experience, including AI/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 for AI infrastructure.

Skills

AI security

Security engineering

Python

LLM internals

Cloud security

Threat modeling

Cryptography

Adversarial ML

Communication skills

Education

Bachelor’s degree in Computer Science

Master’s degree in Cybersecurity

Tools

Threat modeling tools

Job description

Bright Vision Technologies is seeking an AI Governance Engineer to lead security design across AI systems, models, and data pipelines. You will implement controls, perform threat modeling, and shape incident response capabilities tailored to LLMs and AI-powered applications.

The role requires deep security engineering fundamentals, hands-on experience securing AI infrastructures, and strong communication skills to collaborate with product and engineering teams.