Note: The job is a remote job and is open to candidates in USA. Snowflake is a data and AI cloud company powering the era of the agentic enterprise. The Senior Security Engineer will lead and architect product security incident response capabilities focused on AI and LLM security across Cortex AI, Snowflake Intelligence, agentic systems, and supporting data pipelines. The role includes developing detection, containment, and remediation strategies, integrating security into AI product development, and building automated response tooling for emerging AI threats.
Responsibilities
- Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads
- Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment
- Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers
- Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from the ground up
- Represent the IR team to cloud engineering, AI platform teams, corporate security, and customer-facing business units
- Secure modern AI-native codebases operating across multi-cloud environments - including container-based inference services, RAG pipelines, vector stores, and agent orchestration layers
- Partner with world-class AI and security engineering teams, providing expert guidance on secure architecture for high-impact AI features and customer-facing AI capabilities
- Design and manage response capabilities built into Snowflake's AI operational infrastructure - from model serving endpoints to Cortex Search indexes and Snowpark ML pipelines
- Lead with data, code, and automation - build tooling that accelerates detection and response for product security incidents at Snowflake scale
- Drive meaningful security outcomes for the customers and enterprises trusting Snowflake with their most sensitive data and AI workloads
Skills
- Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads
- Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment
- Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers
- Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from the ground up
- Represent the IR team to cloud engineering, AI platform teams, corporate security, and customer-facing business units
- Secure modern AI-native codebases operating across multi-cloud environments - including container-based inference services, RAG pipelines, vector stores, and agent orchestration layers
- Partner with world-class AI and security engineering teams, providing expert guidance on secure architecture for high-impact AI features and customer-facing AI capabilities
- Design and manage response capabilities built into Snowflake's AI operational infrastructure - from model serving endpoints to Cortex Search indexes and Snowpark ML pipelines
- Lead with data, code, and automation - build tooling that accelerates detection and response for product security incidents at Snowflake scale
- Drive meaningful security outcomes for the customers and enterprises trusting Snowflake with their most sensitive data and AI workloads
- 5+ years of experience in information security, primarily in incident response, security engineering, or product/application security
- Direct experience serving as incident commander for product focused security incidents
- Experience leading or actively building an application or security engineering program, with a 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 supply chain attacks on AI dependencies
- Familiarity with the unique data governance and security challenges introduced by LLMs, RAG architectures, and agentic systems
- Working knowledge of cloud-native environments (AWS, Azure, GCP) and the threat landscape specific to SaaS and AI platforms
- SQL proficiency, plus experience building automation and tools with common programming languages (Python preferred)
- 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
- Bachelor's degree in Computer Science or a related field, or equivalent experience
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