Senior AI Security Engineer

CookUnity is a platform that connects the world with great food from chefs. The role involves leading initiatives to integrate AI into security practices and providing governance for AI adoption across the business, ensuring the protection of employees, customers, and the organization from AI threats.

Responsibilities:

• Build and deploy AI/LLM-powered tooling to accelerate security workflows — alert triage, incident investigation, threat detection, and log analysis
• Develop AI agents and automations that reduce manual toil in the SOC (e.g., enrichment, summarization of detections, first-pass triage)
• Integrate AI capabilities into existing security tooling (SIEM, EDR/CrowdStrike, vulnerability management, phishing analysis)
• Partner with engineering teams to integrate AI-assisted secure coding, code review, and vulnerability detection into the development lifecycle
• Build guardrails and automated security checks into AI-assisted coding tools and CI/CD pipelines
• Assess and secure AI/ML components that engineering teams ship in products (prompt injection, model abuse, data leakage, insecure output handling)
• Develop reference patterns and paved-road tooling so developers can adopt AI securely by default
• Threat-model AI-enabled features and applications, mapping to frameworks like the OWASP LLM Top 10 and MITRE ATLAS
• Define and maintain the organization's AI acceptable-use policy and secure-adoption standards
• Establish a review/intake process for evaluating and approving new AI tools, vendors, and use cases
• Assess data-handling and privacy risks of AI tools (what data goes where, training/retention terms, regional compliance)
• Align AI governance with regulatory and framework requirements (e.g., NIST AI RMF, ISO/IEC 42001, SOC 2, PCI DSS where applicable)
• Educate and enable employees on safe AI use through training, guidance, and clear escalation paths

Requirements:

• Bachelor's degree in Computer Science, Cybersecurity, or related field
• 6-8+ years of experience in application security, secure coding, and vulnerability assessment
• Hands-on experience building or deploying AI/LLM-powered tooling, agents, or automations — ideally in a security or engineering context
• Understanding of AI/ML-specific threats and mitigations: prompt injection, data poisoning, model abuse, insecure output handling, data leakage (OWASP LLM Top 10, MITRE ATLAS)
• Demonstrated experience securing software in a modern SDLC (CI/CD, cloud-native environments)
• Ability to assess third-party AI vendors for data-handling, privacy, and security risk
• Ability to work effectively with development teams, guiding and holding them accountable for timely vulnerability remediation
• Self-directed and curious; stays current in a fast-moving AI threat and tooling landscape
• Bias toward enablement — builds paved roads and guardrails rather than blockers
• Fluency in English