Senior Security Engineer (Incident Response)

Join Snowflake as a Senior Security Engineer focused on Product Security Incident Response. In this role, you will lead and architect Snowflake's incident response strategy, with a primary focus on AI and LLM security. You will design, plan, and implement incident response capabilities across Snowflake's AI product surface, lead incident response for product-level security events, and integrate incident response into AI product pipelines. You will also develop and codify the AI abuse response strategy, address tech debt across the AI product stack, and represent the incident response team to various stakeholders.

• Lead and architect Snowflake's product-integrated Incident Response strategy, focusing on AI and LLM security.
• Design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface.
• Develop and codify our AI abuse response strategy, defining detection, containment, and remediation playbooks for LLM misuse.

• Strong communication skills, with the ability to translate security risk into actionable guidance for product teams
• Empathy for developer experience, helping AI engineers ship securely rather than slowing them down
• SQL proficiency, plus experience building automation and tools with common programming languages (Python preferred)
• Experience leading or actively building an application or security engineering program, with a clear point of view on securing AI/ML systems
• Direct experience serving as incident commander for product focused security incidents
• Working knowledge of cloud-native environments (AWS, Azure, GCP) and the threat landscape specific to SaaS and AI platforms
• 5+ years of experience in information security, primarily in incident response, security engineering, or product/application security (preferred)
• Experience with threat modeling and security testing across AI attack surfaces, including prompt injection, indirect injection, model inversion, embedding extraction, and supply chain attacks on AI dependencies
• Bachelor's degree in Computer Science or a related field, or equivalent experience
• Familiarity with the unique data governance and security challenges introduced by LLMs, RAG architectures, and agentic systems
• Experience securing AI/ML infrastructure, including model serving, vector databases, embedding pipelines, API gateways, and LLM-integrated application architectures
• Experience building agentic incident response capabilities, including skills, agents, and pipelines
• Familiarity with CI/CD and secure release lifecycle patterns, with an emphasis on building security into AI feature pipelines
• Understanding of current attacker TTPs, including emerging AI-specific techniques such as adversarial ML, agent manipulation, and LLM jailbreaking in enterprise contexts
• Preferred certifications: GCIA, GCIH, GCSA, GDAT, CISSP/GISP, or cloud certifications (AWS, Azure, GCP)