Senior Manager, AI Red Team

Summary: AI Red Team Senior Manager   Overview   The AI Red Team Senior Manager is The Coca-Cola Company's dedicated adversarial testing specialist for AI systems. This role systematically probes the Company's AI models, AI-enabled applications, and AI infrastructure for vulnerabilities, ensuring that AI deployments across the enterprise are resilient against adversarial manipulation, misuse, and emerging attack techniques. The focus is on AI-specific adversarial testing — not traditional network or application penetration testing — covering risks such as prompt injection, jailbreaking, data poisoning, model exfiltration, training data leakage, and abuse of agentic AI capabilities.   Reporting to the Senior Director, AI Cyber Programs and Emerging Technology, this is a senior individual-contributor role that combines deep   expertise   in AI/ML systems with offensive security tradecraft applied to the AI domain. The Senior Manager designs and executes AI red team engagements, develops testing methodologies and tooling, and delivers clear, actionable findings that enable the Company to harden its AI systems before and after deployment. The role partners with AI governance, development teams, and external specialists (including consultants and bug bounty programs) to ensure comprehensive adversarial coverage of the Company's AI portfolio.

AI Adversarial Testing & Red Teaming   Plan and execute adversarial testing engagements against the Company's AI models, LLM-based applications, agentic AI systems, and AI infrastructure.   Test for AI-specific vulnerabilities including prompt injection, jailbreaking, output manipulation, data poisoning, model inversion, training data extraction, membership inference, and adversarial evasion.   Evaluate the security of AI system architectures, including model hosting, API exposure, data pipelines, fine-tuning workflows, and agent tool-use chains.   Assess risks introduced by third-party AI components, vendor-embedded AI, and AI-enabled SaaS products.   Methodology & Tooling Development   Develop and   maintain   AI red team methodologies, playbooks, and testing frameworks aligned with NIST AI RMF, MITRE ATLAS, OWASP Top 10 for LLMs, and emerging industry standards.   Build and   maintain   custom tooling, scripts, and automation for AI adversarial testing, including prompt fuzzing, model probing, and automated vulnerability scanning of AI systems.   Evaluate and integrate open-source and commercial AI security testing tools (such as Garak,   PyRIT , or similar) into the testing workflow.   Stay current with the latest AI adversarial research, published attacks, and defensive techniques.   AI Security Controls Assessment   Assess the effectiveness of AI security controls, including input/output filtering, content moderation, guardrails, access controls, logging, and monitoring.   Evaluate human oversight mechanisms, model governance processes, and incident response readiness for AI-specific security events.   Test the resilience of AI systems under adversarial conditions, including coordinated multi-step attacks and advanced jailbreak chains.   Recommend proportionate controls and mitigations based on testing results, risk severity, and the Company's AI risk appetite.   External Partnerships & Coordination   Coordinate with external consultants, specialized AI security firms, and bug bounty programs for AI-specific adversarial assessments.   Engage with the AI security research community, industry working groups, and standards bodies to stay current and   contribute   the Company's perspective.   Partner with AI governance, development teams, and business units to ensure testing priorities align with the Company's AI deployment roadmap.   Reporting & Knowledge Building   Produce clear, actionable adversarial testing reports with findings, evidence, risk ratings, and remediation guidance for technical and executive