Job
Description
Role Overview: You will combine expertise in cybersecurity and AI/ML to design, implement, and maintain security frameworks, ensuring the integrity, confidentiality, and compliance of AI-driven solutions throughout their lifecycle. Your role will involve collaborating with cross-functional stakeholders and AI Engineers to build and deploy an enterprise-wide AI security framework. Key Responsibilities: - Design and maintain structured guidelines and controls to secure AI systems, covering data protection, model security, and compliance requirements. - Evaluate and utilize established frameworks such as Google's Secure AI Framework (SAIF), NIST AI Risk Management Framework, or the Framework for AI Cybersecurity Practices (FAICP) as references or baselines. - Identify, assess, and mitigate security risks specific to AI, including adversarial attacks, data poisoning, model inversion, and unauthorized access. - Conduct regular vulnerability assessments and penetration testing on AI models and data pipelines. - Ensure data used in AI systems is encrypted, anonymized, and securely stored. - Implement robust access controls (e.g., RBAC, ABAC, Zero Trust) for sensitive AI data and models. - Protect AI models from tampering, theft, or adversarial manipulation during training and deployment. - Monitor and log AI system activity for anomalies or security incidents. - Develop and enforce policies to ensure AI systems adhere to industry regulations, ethical standards, and organizational governance requirements. - Promote transparency, explainability, and fairness in AI models. - Establish real-time monitoring and advanced threat detection for AI systems. - Develop and maintain an AI incident response plan for prompt mitigation and recovery. - Educate teams on AI security best practices and foster a security-aware culture. - Collaborate with IT, data science, compliance, and business units to align AI security with organizational goals. Qualifications: - Strong understanding of AI/ML concepts, architectures, and security challenges. - Strong programming skills in Python, R, or similar languages. - Strong experience in Google Cloud Platform (GCP) or equivalent. - Solid understanding of machine learning algorithms, neural networks, NLP, and computer vision. - Experience with cloud AI/ML services and deployment pipelines is a plus. - Experience with security frameworks (e.g., SAIF, NIST, FAICP) and regulatory compliance. - Proficiency in data protection techniques, encryption, and secure access management. - Familiarity with adversarial machine learning, model hardening, and input sanitization. - Knowledge of incident response, monitoring tools, and threat intelligence platforms. - Excellent communication and documentation skills for policy development and stakeholder engagement. Additional Details of the Company: Omit as no additional details of the company are mentioned in the provided Job Description. Role Overview: You will combine expertise in cybersecurity and AI/ML to design, implement, and maintain security frameworks, ensuring the integrity, confidentiality, and compliance of AI-driven solutions throughout their lifecycle. Your role will involve collaborating with cross-functional stakeholders and AI Engineers to build and deploy an enterprise-wide AI security framework. Key Responsibilities: - Design and maintain structured guidelines and controls to secure AI systems, covering data protection, model security, and compliance requirements. - Evaluate and utilize established frameworks such as Google's Secure AI Framework (SAIF), NIST AI Risk Management Framework, or the Framework for AI Cybersecurity Practices (FAICP) as references or baselines. - Identify, assess, and mitigate security risks specific to AI, including adversarial attacks, data poisoning, model inversion, and unauthorized access. - Conduct regular vulnerability assessments and penetration testing on AI models and data pipelines. - Ensure data used in AI systems is encrypted, anonymized, and securely stored. - Implement robust access controls (e.g., RBAC, ABAC, Zero Trust) for sensitive AI data and models. - Protect AI models from tampering, theft, or adversarial manipulation during training and deployment. - Monitor and log AI system activity for anomalies or security incidents. - Develop and enforce policies to ensure AI systems adhere to industry regulations, ethical standards, and organizational governance requirements. - Promote transparency, explainability, and fairness in AI models. - Establish real-time monitoring and advanced threat detection for AI systems. - Develop and maintain an AI incident response plan for prompt mitigation and recovery. - Educate teams on AI security best practices and foster a security-aware culture. - Collaborate with IT, data science, compliance, and business units to align AI security with organizational goals. Qualifications: - Strong understanding of AI/ML concepts, architectures, and security challenges. -
