Senior Threat Intelligence Engineer

Cloudflare Cloudflare · Enterprise · Austin, TX · Security

This role involves applying machine learning and threat intelligence to build automated defenses against cyber threats. The engineer will be responsible for the full ML lifecycle, from data ingestion to inference, and integrating various security tools to streamline operations and reduce detection/response times.

What you'd actually do

  1. Proactively research, collect, and analyze threat intelligence from various sources (OSINT, commercial feeds, dark web, and internal security events) to understand the current and emerging threat landscape.
  2. Design, implement, and maintain detection use cases for the entire machine learning lifecycle (data ingestion, training, deployment, and inference).
  3. Develop detailed profiles of relevant threat actors, their Tactics, Techniques, and Procedures (TTPs) using frameworks like MITRE ATT&CK , and identify potential impacts to the organization.
  4. Produce and disseminate timely, relevant, and actionable intelligence reports and briefings for both technical security teams and executive leadership.
  5. Engineer the ingestion, enrichment, correlation, and contextualization of Indicators of Compromise (IOCs) and Indicators of Attack (IOAs) into security platforms.

Skills

Required

  • Threat Intelligence (TI)
  • Machine Learning
  • engineering principles
  • Python
  • MITRE ATT&CK
  • SOAR

Nice to have

  • attacker Tools, Techniques and Procedures (TTPs)
  • attack components
  • threat hunting
  • data gathering and analysis
  • security event information
  • nation state motivations and operational capabilities
  • Infrastructure-as-Code (IaC)
  • Terraform
  • data analysis and visualization tools for threat intelligence
  • malware analysis

What the JD emphasized

  • machine learning data science
  • Machine Learning
  • machine learning lifecycle
  • threat intelligence

Other signals

  • applying advanced Machine Learning and engineering principles
  • transform raw threat data into actionable security measures and automated defenses
  • design, implement, and maintain detection use cases for the entire machine learning lifecycle (data ingestion, training, deployment, and inference)