Staff Security Engineer

• Take end-to-end ownership of the GTI Agentic data layer, defining the technical strategy, architecture, and governance for curating and structuring multi-modal security datasets across Google Threat Intelligence.
• Design, architect, and build novel investigative tools, link-analysis frameworks, and data-mining pipelines to discover previously unseen relationships, campaign clusters, and threat actor patterns across massive internal and external security datasets.
• Own the quality, fidelity, taxonomy, and ground truth of our AI and autonomous agent evaluation frameworks (evals), ensuring benchmarks accurately reflect real-world malware reversing, threat hunting, deobfuscation, and CTI workflows.
• Act as the primary technical stakeholder and liaison for partner organizations, aligning roadmaps, co-designing agentic skills, and integrating front-line threat intelligence and reverse engineering workflows into the agentic platform.
• Solve complex, zero-to-one data engineering bottlenecks, such as distinguishing true agentic reasoning failures from dataset artifacts.

Minimum qualifications:

• Bachelor's degree in Computer Science, Data Science, Information Security, a related technical field, or equivalent practical experience.
• 8 years of experience in security engineering, CTI, or security data analysis, and software development in Python, Go, or C++.
• Experience in CTI, threat actor tracking, malware analysis, or threat hunting, and modeling and analyzing security datasets.

Preferred qualifications:

• Extensive experience working directly with or embedded alongside front-line threat intelligence and reverse engineering teams to operationalize adversary tradecraft into structured datasets and automated tooling.
• Experience building and scaling ground-truth evaluation datasets, trajectory grading pipelines, and agentic benchmarking frameworks.
• Experience analytically owning large-scale data layers, data quality pipelines, or evaluation/benchmarking frameworks for AI/ML systems, LLMs, or autonomous agents.
• Deep expertise in graph analytics, knowledge graphs, clustering, embeddings, and petabyte-scale data processing engines (e.g., BigQuery, Cloud Spanner, distributed data pipelines) applied to threat intelligence corpora.

• Bachelor's degree in Computer Science, Data Science, Information Security, a related technical field, or equivalent practical experience.
• 8 years of experience in security engineering, CTI, or security data analysis, and software development in Python, Go, or C++.
• Experience in CTI, threat actor tracking, malware analysis, or threat hunting, and modeling and analyzing security datasets.