Senior Threat Intelligence Engineer

Cloudflare•San Francisco, CA

About The Position

We are seeking an experienced Threat Intelligence Engineer with experience with machine learning data science to join our proactive security team. This role is a critical blend of two disciplines: leveraging Threat Intelligence (TI) to understand the adversary, and then applying advanced Machine Learning and engineering principles to rapidly and effectively defend our organization. The ideal candidate will transform raw threat data into actionable security measures and automated defenses, significantly reducing our mean time to detect (MTTD) and mean time to respond (MTTR) to sophisticated cyber threats.

Requirements

4+ years of hands-on experience in a Security Engineering, Cyber Threat Intelligence, or Security Automation role.
Strong proficiency in at least one scripting/programming language for automation (e.g., Python ).
Deep understanding of the cyber kill chain, threat actor TTPs, common attack vectors, networking protocols, and operating system internals.
Proven experience designing and implementing SOAR playbooks and integrating security tools via APIs.
Experience working with commercial and open-source Threat Intelligence Platforms (TIPs) and threat feeds.
Familiarity with security services and automation in major cloud environments (AWS, Azure, or GCP).

Nice To Haves

Understanding of attacker Tools, Techniques and Procedures (TTPs)
Understanding of attack components
Experience threat hunting in a complex network
The ability to read an attack brief or vulnerability report and contextualize the associated risk
Experience validating vulnerability reports and providing impact analysis
Experience performing data gathering and analysis on perceived threats; generating additional contextual data that can be operationalized
Experience with common tools used within Security Operations
Experience utilizing security event information in intelligence analysis
Ability to navigate ambiguity, and provide clarity to complex situations
Ability to work autonomously with a strong sense of urgency, ownership and self drive
Ability to build partnerships and get results across many different stakeholders
Ability to effectively communicate, both verbal and written, to stakeholders regarding relative risk, urgency, and feedback
Highly qualified candidates will have an understanding of nation state motivations and operational capabilities
Experience with Infrastructure-as-Code (IaC) tools like Terraform.
Familiarity with data analysis and visualization tools for threat intelligence
Experience with malware analysis and reverse engineering to extract actionable indicators.

Responsibilities

Intelligence Collection & Analysis: 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.
Machine Learning and Data Science: Design, implement, and maintain detection use cases for the entire machine learning lifecycle (data ingestion, training, deployment, and inference).
Threat Actor Profiling: 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.
Actionable Intelligence Dissemination: Produce and disseminate timely, relevant, and actionable intelligence reports and briefings for both technical security teams and executive leadership.
IOC/IOA Management: Engineer the ingestion, enrichment, correlation, and contextualization of Indicators of Compromise (IOCs) and Indicators of Attack (IOAs) into security platforms.
Automated Defense Development: Design, develop, and implement robust automation workflows and playbooks (SOAR) to streamline security operations tasks, including incident triage, alert enrichment, vulnerability management, and threat response actions.
Tool Integration & Optimization: Integrate diverse security tools (e.g., SIEM, EDR, Cloud Security Posture Management, vulnerability scanners, Threat Intelligence Platforms) through APIs and scripting (primarily Python) to create seamless, automated feedback loops.
Process Improvement: Identify manual, repetitive, and time-consuming security processes and engineer scalable automation solutions to increase team efficiency and operational maturity.
Incident Response Support: Provide threat context to support the Incident Response team during active security incidents.
Cross-Functional Partnership: Collaborate with Detection Engineers, Security Engineers, and Software Developers to embed security and intelligence-driven practices into the CI/CD pipeline and corporate infrastructure.