Senior Security Engineer (AI Security)

Location: Remote, United States

Salary: $176K–$253K annually

Company

Snowflake provides cloud data and AI products used by enterprises for sensitive data and AI workloads.

What you will do

• Lead product-level security incident response, including incident commander responsibilities for AI-specific events.
• Architect and integrate incident response capabilities across Cortex AI, Cortex Agents, Snowflake Intelligence, and AI-powered developer experiences.
• Develop detection, containment, and remediation playbooks for prompt injection, model abuse, agent hijacking, adversarial inputs, and data exfiltration.
• Secure multi-cloud AI systems, including container-based inference services, RAG pipelines, vector stores, model-serving endpoints, and agent orchestration layers.
• Build automation and tooling to accelerate detection and response for product security incidents.
• Partner with AI, security, cloud engineering, and product teams to embed security requirements from design through deployment.

Requirements

• 5+ years of experience in information security, incident response, security engineering, or product/application security.
• Experience leading or building security engineering or application security programs, with expertise in securing AI/ML systems.
• Experience with threat modeling and security testing for prompt injection, indirect injection, model inversion, embedding extraction, and AI supply-chain attacks.
• Knowledge of LLM, RAG, and agentic-system security, data governance, attacker TTPs, adversarial ML, agent manipulation, and LLM jailbreaking.
• Working knowledge of AWS, Azure, GCP, SaaS security, SQL, Python, automation, CI/CD, and secure release lifecycle practices.
• Bachelor's degree in Computer Science or a related field, or equivalent experience.

Nice to have

• Experience securing model-serving infrastructure, vector databases, embedding pipelines, API gateways, and LLM-integrated applications.
• Experience building agentic incident response capabilities involving skills, agents, and pipelines.
• GCIA, GCIH, GCSA, GDAT, CISSP/GISP, or AWS, Azure, or GCP certifications.

Culture & Benefits

• High-impact security work focused on emerging AI and LLM threats.
• Close collaboration with AI and security engineering teams.
• Opportunity to shape incident response practices for AI-native systems used by enterprise customers.
• AI-native, experimental working environment emphasizing rapid testing, practical automation, and low-ego collaboration.