Security Engineer (AI)

TL;DR

Security Engineer (AI): Enhancing Snowflake’s Threat Detection Program by building, maintaining, and evolving detections and supporting pipelines with AI and automation. Focus on mitigating identified risks, making data-driven decisions, and designing AI-driven workflows to enhance security posture.

Location: Remote (US)

Salary: $122K – $174.8K

Company

Snowflake has developed a world class cloud data platform that is effective, affordable and accessible to all data users.

What you will do

• Develop and deploy detections using modern engineering practices, including rules-based and AI-assisted detections.
• Mature the threat detection program by analyzing gaps and mitigating risks via detective controls, including experimentation with AI/ML approaches.
• Build and maintain strong partnerships with stakeholders to provide detection as a service, including self-service patterns, reusable components, and AI-enhanced detections.
• Continuously measure and improve detection quality (coverage, precision/recall, false positive rate, latency).

Requirements

• Security Engineering Experience (Threat Detection, Incident Response, Threat Hunting, Product Security, Corporate Security, or other related disciplines).
• Solid experience writing code in Python, Go, etc., with a desire to apply these skills to AI/ML-powered use cases in detection and response.
• Experience collaborating with various security teams and stakeholders.
• Ability to review and analyze logging and observability requirements that support detection and response.
• Knowledge of the current security landscape with domain knowledge in cloud security, identity and access, SaaS security, endpoint security, data security, and insider risk.
• An automation-first mindset for scaling security, including comfort with CI/CD, infrastructure as code, and “detections as code.”

Nice to have

• Computer Science degree or equivalent practical experience.
• Experience developing and working with systems that utilize infrastructure as code (e.g., Terraform, CloudFormation), and/or “detections as code” frameworks.
• Experience building and maintaining production-level software or platforms that process high-volume data streams or power security analytics.
• Experience deploying detections at a global scale.
• Experience with Snowflake or equivalent cloud data platforms, including building data pipelines or analytics that could support security workloads.

Culture & Benefits

• Laser focused on doing security in the agentic era.
• Strong demand from customers and strong support from the business for security.
• Great team with a diverse set of backgrounds and skills.
• Opportunity for impact on both Snowflake and the broader security ecosystem.