About the role

AI Infrastructure Security Engineer assessing AI deployment architectures and conducting security testing. Collaborating with engineering teams to ensure AI products meet enterprise security standards.

Responsibilities

Review and assess AI deployment architectures across cloud environments
Conduct infrastructure-level security testing for API exposure
Conduct infrastructure-level security testing for Authentication & authorization controls
Conduct infrastructure-level security testing for Secrets and key management
Conduct infrastructure-level security testing for Data encryption in transit and at rest
Conduct infrastructure-level security testing for Logging and monitoring configurations
Evaluate RAG pipelines, vector databases, and embedding workflows
Identify vulnerabilities across model hosting environments
Identify vulnerabilities across containerized deployments
Identify vulnerabilities across CI/CD pipelines
Identify vulnerabilities across third-party integrations
Partner with engineering and security teams to validate remediations
Align findings to enterprise security frameworks where applicable
Produce structured documentation suitable for internal security and compliance teams

Strong background in cloud security (AWS, Azure, or GCP)
Experience securing API-based systems
Knowledge of container security (Docker, Kubernetes)
Familiarity with identity and access management models
Experience with encryption standards and key management
Strong understanding of DevSecOps principles
Exposure to AI/ML deployment environments
Familiarity with LLM API architectures
Familiarity with RAG systems
Familiarity with vector databases
Understanding of data governance within AI workflows
Experience working within ISO 27001 or SOC 2 environments
Understanding of cloud security control frameworks (ISO 27017 helpful)
Ability to communicate findings clearly to both engineering and governance teams