Security Architect - AI Technologies

2w2 weeks ago

Commvault

US · Full-time · $72,250 – $195,500

About this role

Commvault is the gold standard in cyber resilience, empowering customers to recover from cyberattacks with its AI-powered platform for data protection, security, and intelligence. As Security Architect focused on AI, secure design and deployment of AI- and ML-enabled systems across internal environments. This hands-on role identifies and mitigates security risks unique to AI while enabling innovation.

You will identify security risks in AI/ML systems, models, data pipelines, and integrations. Define and implement controls for AI development, training, deployment, and inference environments. Assess risks like data leakage, model abuse, prompt injection, and unauthorized access.

Partner closely with Enterprise Architecture, Security Engineering, and Cloud Security teams for security reviews of AI-enabled products and workflows. Embed security into AI design reviews, threat modeling, and SDLC processes. Secure AI-related data sources, training datasets, and model artifacts.

Evaluate third-party AI services for security and compliance risks. Develop guidance, standards, and guardrails for secure AI usage. Monitor emerging AI threats and support incident response involving AI systems.

Requirements

5+ years of experience in information security, product security, or security engineering roles
Strong communication ability to work with both technical stakeholders and leadership
Strong, structured writing ability needed to conduct security reviews
Strong understanding of application security fundamentals and secure SDLC practices
Strong understanding of securing AI-related authentication and authorization mechanisms (OAuth 2.0, OIDC, general token management)
Familiarity with AI/ML concepts, workflows, and common architectures
Familiarity with MCP, tools and AI policy guardrails
Familiarity with LLM security risks (e.g., prompt injection, data poisoning, model extraction)

Responsibilities

Identify and assess security risks associated with AI/ML systems, models, data pipelines, and integrations
Define and implement security controls for AI development, training, deployment, and inference environments
Partner with engineering teams to embed security into AI design reviews, threat modeling, and SDLC processes
Assess and mitigate risks such as data leakage, model abuse, prompt injection, and unauthorized access
Secure AI-related data sources, training datasets, and model artifacts
Evaluate third-party AI services and integrations for security and compliance risk
Develop guidance, standards, and guardrails for secure and responsible AI usage
Monitor emerging AI threats and vulnerabilities and translate them into actionable controls