Job Description
AI/ML Security Assessments & Risk Management
Conduct comprehensive security assessments of AI/ML systems, including data pipelines, model training environments, inference endpoints, and MLOps workflows.
Identify complex risks related to data privacy, data leakage, adversarial attacks, model poisoning, prompt injection, and misuse of AI technologies.
Evaluate threats across the AI lifecyclefrom data collection to model retirementand define appropriate mitigation actions.
AI Governance & Security Controls
Develop and implement security controls, governance frameworks, and policies for end-to-end AI lifecycle management.
Support clients in complying with AI regulations, responsible AI principles, and data protection requirements (e.g., GDPR, NIST AI RMF).Create strategic roadmaps and executive-level recommendations for secure AI adoption.
Cloud & Infrastructure Security for AI
Design secure cloud architectures for AI workloads across AWS, Azure, and GCP.Implement best practices for IAM, encryption, secrets management, container security, network segmentation, and secure data storage.
Assess and secure APIs, microservices, and application components that support AI models and intelligent systems.
Identity & Access Management for AI Agents
Design IAM models for AI agents, including agent identities, delegated permissions, ephemeral credentials, and cross-system trust boundaries.
Implement zero-trust principles for agent authentication, authorization, and privilege controls.Develop patterns for scoped access, JIT (Just-In-Time) authorizations, short-lived tokens, and decoupled privilege elevation.
Integrate IAM systems with AI agent orchestration and establish access governance processes, including permission reviews, certifications, and usage monitoring.
Client Communication & Advisory
Translate technical security risks into clear business impacts that executive stakeholders can act on.Prepare assessment reports, recommendations, threat models, and remediation plans for clients.
Work cross-functionally with AI engineers, data scientists, IT security, and compliance teams to deliver secure AI solutions.
Required Skills & Qualifications
38+ years of experience in cybersecurity, cloud security, or data security roles.
Demonstrated experience securing AI/ML platforms, models, pipelines, or agent-based systems.Strong knowledge of cloud security (AWS, Azure, GCP), IAM, network security, encryption, and API security.
Understanding of AI threats such as adversarial ML, data contamination, and model theft.Experience with container platforms (Docker, Kubernetes) and MLOps tools (SageMaker, Vertex AI, Azure ML, MLflow).
Excellent analytical and communication skills, with the ability to present findings to technical and non-technical audiences.
Preferred Qualifications
Certifications such as CCSP, CISSP, CCIE, AWS/Azure/GCP Security Specialty, or AI governance credentials.
Experience in responsible AI, AI policy, or AI compliance frameworks.
Background in security engineering, threat modeling, or red teaming for AI systems.
Experience working in consulting organizations or large enterprise security programs.
