AI Governance Engineer

Accountabilities

• Lead the development of security frameworks and governance practices for AI and machine learning systems.
• Help identify emerging threats, design defensive strategies, and ensure AI-powered applications are secure, reliable, and aligned with industry best practices.
• Design and implement security controls, governance frameworks, and protection strategies for AI and machine learning systems.
• Develop threat models and security architectures specifically tailored to LLMs, AI applications, model APIs, and training data pipelines.
• Identify and mitigate AI-specific security risks including prompt injection, model abuse, data exfiltration, and supply chain vulnerabilities.
• Conduct security reviews of AI-powered applications and supporting infrastructure.
• Establish incident response capabilities for AI-related security events.
• Analyze AI system vulnerabilities and develop practical defense mechanisms.
• Collaborate with engineering, cybersecurity, and technology teams to integrate secure AI practices throughout development lifecycles.
• Support responsible AI adoption by helping teams understand risks, controls, and governance requirements.
• Contribute to continuous improvement of AI security standards, processes, and best practices.

Requirements

• Combine strong cybersecurity expertise with practical knowledge of modern AI systems.
• Have experience designing security solutions, analyzing complex technical risks, and applying security principles to emerging AI technologies.
• Hold a Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or a related technical discipline.
• Have 6+ years of security engineering experience, including significant experience with AI or machine learning systems.
• Strong understanding of LLM architectures, AI system components, and common AI security failure modes.
• Hands-on experience designing security controls for AI-powered applications.
• Strong knowledge of application security, identity management, cryptography, and cloud security principles.
• Experience with threat modeling, security architecture reviews, and risk assessment processes.
• Familiarity with adversarial machine learning, prompt injection techniques, and AI model abuse research.
• Proficiency in Python and experience with at least one systems programming language.
• Strong understanding of modern cloud infrastructure security practices.
• Excellent written and verbal communication skills.
• Experience with AI security research, LLM red teaming, CTF participation, publications, or open-source security projects is preferred.
• Familiarity with privacy-preserving machine learning techniques such as differential privacy is a plus.
• Experience working in regulated industries with strict data protection requirements is beneficial.

Benefits

• A competitive annual salary range of $100,000-$150,000.
• A fully remote work opportunity across the United States.
• A full-time direct employment opportunity.
• Opportunity to work on advanced AI security and governance initiatives.
• Exposure to emerging technologies across artificial intelligence, cybersecurity, and cloud infrastructure.
• Career growth opportunities within a technology-focused environment.
• A flexible remote work environment supporting professional growth and work-life balance.