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Staff Security Engineer (Threat Detection)

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Onsite

Staff Security Engineer (Threat Detection)

Snowflake

Staff Security Engineer (Threat Detection)

Skills

Google Cloud PlatformSQL QueriesPythonGolangData ScienceGitData AnalysisMachine LearningAIAWSSupply ChainTerraformAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

$211,000 – $303,600 / year

Location:

United States

Work mode:

Onsite

Published on:

13 August 2026

What they need


  • We are hiring a Staff Security Engineer, Threat Detection for our Security team
  • As Snowflake scales globally, we are investing heavily in AI-powered threat detection and response to protect our customers and our environment at cloud scale
  • This role helps enhance and extend the reach of Snowflake’s Threat Detection Program, with AI and automation as core primitives in how we detect, triage, and respond to threats
  • You will combine deep security expertise with strong engineering skills to build, maintain, and evolve detections and the pipelines that support them, partnering with stakeholders across Security and Engineering to make informed, data-driven decisions grounded in threat models, proactive threat hunts, and exploration of logs and telemetry
  • Develop and deploy detections using modern engineering practices (testing and validation, CI/CD pipelines, detections as code, and a full detection development lifecycle), spanning both rules-based and AI-assisted detections
  • Mature our threat detection program by analyzing coverage gaps and mitigating risks through detective controls, experimenting with AI/ML approaches where they improve signal-to-noise ratio or analyst efficiency
  • Make data-driven recommendations for detective and preventative controls based on threat models, proactive threat hunts, and data science-oriented exploration of logs and telemetry
  • Design and build automations and AI-driven workflows that strengthen our security posture and reduce mean time to detect and respond
  • Build and maintain strong partnerships with stakeholders to deliver detection as a service, including self-service patterns, reusable components, and AI-enhanced detections that support their domains
  • Continuously measure and improve detection quality across coverage, precision and recall, false positive rate, and latency

Benefits

  • Comprehensive health insurance plans
  • Health savings accounts
  • Robust retirement plans
  • Life and disability insurance
  • Weekly online lunch and learns
  • Virtual workout classes
  • Ergonomic work-from-home equipment
  • On-demand mental health and wellness programs
  • Fertility benefits and family planning resources
  • Generous time-off and various leave plans
  • Onsite and Remote Work
  • Employee discounts and pre-tax selections
  • New hire equity + Employee Stock Purchase Plan (ESPP)
  • Quarterly bonus or commission program- 8+ years of security engineering experience across one or more of threat detection, incident response, threat hunting, product security, or corporate security, or equivalent experience
  • Strong coding ability in a high-level language such as Python or Go, with a track record of building software, data tooling, or automations, and a desire to apply those skills to AI/ML-powered detection and response
  • Familiarity with the risks that impact SaaS products and workstations, such as account compromise, data exfiltration, phishing, and supply chain attacks
  • A risk-based approach that helps prioritize key security initiatives and judge when AI provides meaningful value over traditional rules and heuristics, paired with a humble, team-oriented mindset in a zero-ego environment
  • Experience handling data programmatically (SQL, Python), ideally including large-scale log and telemetry datasets used for detection logic or analytics
  • Experience writing production code, including unit tests, version control, and CI/CD integration
  • Experience developing and operating agent-based or agentic workflows (for example, LangGraph or similar orchestration frameworks)
  • Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) and a solid understanding of its native logging, monitoring, and security services
  • Experience with infrastructure as code (Terraform, CloudFormation) and/or detections-as-code frameworks
  • Experience applying GenAI and LLM-based approaches to security workflows, such as detection engineering, alert triage, enrichment, or summarization
  • Computer Science degree or equivalent practical experience
  • Experience deploying detections at global scale
  • Experience building and maintaining production software or platforms that process high-volume data streams (logs, metrics, traces) or power security analytics
  • Experience with Snowflake or equivalent cloud data platforms, including building data pipelines or analytics that support security workloads, and interest in Snowflake Cortex AI or similar in-platform AI capabilities

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