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• Lead incident response for product-level security events focused on AI-specific threats such as prompt injection, model abuse, agent hijacking, and AI-enabled data exfiltration


• Integrate incident response into Cortex, Snowflake Intelligence, and AI-powered developer experience pipelines from design through deployment


• Develop detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks


• Address security and incident-response readiness technical debt across the AI product stack


• Represent incident response to cloud engineering, AI platform, corporate security, and customer-facing business units


• Secure AI-native codebases across multi-cloud environments, including inference services, RAG pipelines, vector stores, and agent orchestration layers


• Advise AI and security engineering teams on secure architecture for high-impact AI features


• Design and manage response capabilities across model-serving endpoints, Cortex Search indexes, and Snowpark ML pipelines


• Build data-, code-, and automation-driven tooling to accelerate product security incident detection and response


• Drive security outcomes for customers and enterprises using Snowflake AI workloads

• 5+ years of experience in information security, primarily incident response, security engineering, or product/application security (preferred)


• Direct experience serving as incident commander for product-focused security incidents


• Experience leading or actively building an application or security engineering program


• Clear point of view on securing AI/ML systems


• Experience with threat modeling and security testing across AI attack surfaces, including prompt injection, indirect injection, model inversion, embedding extraction, and AI dependency supply-chain attacks


• Familiarity with data governance and security challenges involving LLMs, RAG architectures, and agentic systems


• Working knowledge of AWS, Azure, GCP, SaaS platforms, and AI platform threats


• SQL proficiency


• Experience building automation and tools with common programming languages, Python preferred


• Strong communication skills for translating security risk into actionable product-team guidance


• Bachelor's degree in Computer Science or a related field, or equivalent experience


• Bonus: experience securing AI/ML infrastructure, model serving, vector databases, embedding pipelines, API gateways, and LLM-integrated applications


• Bonus: experience building agentic incident response capabilities


• Bonus: understanding of attacker TTPs, adversarial ML, agent manipulation, and LLM jailbreaking


• Bonus: familiarity with CI/CD and secure AI release lifecycle patterns


• Preferred certifications include GCIA, GCIH, GCSA, GDAT, CISSP/GISP, or AWS, Azure, or GCP certifications

Demonstrates expertise in incident response for AI-specific security threats, including prompt injection and model abuse, while integrating security practices into multi-cloud environments. Proficient in developing playbooks and tooling for AI security, with strong communication skills to guide product teams on security risks.

• Incident Response Leadership


• AI/ML Security Expertise


• Threat Modeling and Security Testing


• Automation and Tool Development


• Cloud Security Knowledge

• Incident Response


• Security Engineering


• Threat Modeling


• SQL Proficiency


• Python Programming


• AI/ML Security


• Automation Development


• Security Testing


• Data Governance


• Incident Command

• Strong Communication Skills

• GCIA


• GCIH


• GCSA


• GDAT


• CISSP


• GISP


• AWS Certification


• Azure Certification


• GCP Certification

• AI Security


• Incident Response


• Model Serving


• Adversarial ML


• Agent Manipulation


• LLM Jailbreaking


• RAG Architectures


• AI Dependency Supply-Chain Attacks


• Embedding Pipelines


• Agentic Systems

• AWS


• Azure


• GCP


• Cortex


• Snowflake


• SaaS Platforms


• CI/CD


• Vector Databases


• API Gateways


• LLM-integrated Applications