Director, Security Products: Key Management

Responsibilities

• Define and drive DigitalOcean’s AI security strategy, investment priorities, and multi-year roadmap.
• Build, deploy, monitor, and improve AI/ML security models, guardrails, tooling, and automations with Security Data Science and Security Engineering.
• Lead AI red teaming and adversarial testing, including jailbreaking, prompt injection, evasion, and poisoning assessments.
• Review AI product architectures and provide security sign-off and escalation guidance from design through launch.
• Threat-model AI systems across data ingestion, training, fine-tuning, evaluation, model serving, RAG, agent frameworks, and post-deployment monitoring.
• Architect and lead the AI Risk & Governance framework, including policies, standards, and controls.
• Represent AI security in executive and board-level briefings and define positions on emerging AI security topics.

Requirements

• 10+ years of cybersecurity experience, including at least 4–5 years in AI/ML security, adversarial machine learning, or security data science in a production cloud or technology environment.
• Demonstrated organizational ownership of AI or security programs and strategy.
• Practitioner-level knowledge of adversarial ML attacks and defenses, including evasion, poisoning, model extraction, membership inference, and prompt injection.
• Ability to evaluate AI security research and translate it into engineering guidance and organizational policy.
• Experience communicating technical risk and investment decisions to executives and senior leadership.
• Strong programming skills in Python and Go, including building security tooling and automation.
• Experience reviewing AI/ML architectures covering data ingestion, feature engineering, training pipelines, model serving, and continuous monitoring.
• Hands-on experience with AI red-team, defensive, and model supply-chain tooling.
• Bachelor’s or Master’s degree in Computer Science, Information Security, Mathematics, or a related field, or equivalent practical experience.
• Fluency in OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, and the EU AI Act.
• Experience with a cloud provider, security product company, or large-scale internet platform operating AI/ML systems at customer-facing scale.
• Familiarity with production LLM security, including RAG pipelines, agentic frameworks, model APIs, prompt injection, jailbreaking, and data exfiltration.

Benefits

• Remote role.
• Competitive benefits, including an Employee Assistance Program, local employee meetups, and flexible time off, with specifics varying by location.
• Reimbursement for relevant conferences, training, and education, plus access to LinkedIn Learning courses.
• Potential bonus based on company and individual performance.
• Eligible employees may receive equity compensation, equity grants upon hire, and access to an Employee Stock Purchase Program.