Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience leading security assessments, threat modeling, or security design reviews for systems.
• 5 years of coding experience in one or more general purpose languages. (e.g., Python, Golang, Java, C++).
• 5 years of experience with security engineering, computer and network security and security protocols.

Preferred qualifications:

• Experience designing, building, or implementing LLMs and autonomous agent frameworks to accelerate threat detection lifecycles, automate security operations triage, or orchestrate self-healing detection pipelines.
• Experience designing, building, or implementing LLMs and autonomous agent frameworks to accelerate threat detection lifecycles, automate security operations triage, or orchestrate self-healing detection pipelines.
• Experience in security research, advanced threat hunting, and signals development across endpoint or cloud data sources (e.g., Google Cloud, Cloud computing platform, Kubernetes).
• Ability to scope ambiguous security problems, evaluate systemic risks, and communicate technical security strategies effectively to both engineering teams and executive stakeholders.

About the job

There's no such thing as a "safe system" - only safer systems. Our Security team works to create and maintain the safest operating environment for Google's users and developers. As a Security Engineer, you help protect network boundaries, keep computer systems and network devices hardened against attacks and provide security services to protect highly sensitive data like passwords and customer information. Security Engineers work directly with network equipment and actively monitor our systems for attacks and intrusions. You also work with software engineers to proactively identify and fix security flaws and vulnerabilities.

You use your industry experience to own and drive the resolution of complex security incidents, policy questions and technical security issues.

Uppercase is a specialized team of security engineers dedicated to identifying and mitigating threat actors before they can achieve their mission. Originating from Alphabet's moonshot factory, X, and developed within Chronicle (now Google SecOps), we leverage expertise in big data, cybersecurity, machine learning, and large-scale cloud computing to engineer next-generation security solutions. Our goal is to partner with the broader security community to ensure the advantage remains with those fighting cybercrime.

In this role, you will focus on building, scaling, and orchestrating autonomous security operations within Google security operations (SecOps) (formerly Chronicle). You will design and deploy intelligent agentic workflows, including threat hunting agents and automated detection engineering agents, to match the velocity of modern threat actors. By leveraging Google’s internal cloud and endpoint threat intelligence, you will transform static security workflows into self-correcting, LLM-driven pipelines that automate the entire detection lifecycle from discovery to rule deployment.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

• Build and optimize AI-agent frameworks (such as threat hunting and detection engineering agents) to automate triage, context enrichment, and initial threat analysis.
• Construct and manage end-to-end pipelines that autonomously write, test, and tune yet another recursive acronym - log (YARA-L) rules based on emerging threat behavior.
• Conduct deep-dive technical analyses of adversary behavior to extract concrete indicators and logic that train machine learning models and ground agentic workflows.
• Drive continuous refinement of the rule lifecycle by leveraging advanced LLM architectures to automate regression testing, false-positive reduction, and rule deprecation. Perform data analysis on large threat intelligence datasets to uncover hidden patterns, feed ML pipelines, and expand the knowledge base of autonomous systems.
• Create, maintain, and scale the underlying processes and code-driven tooling required to support decentralized, automated security operations.