Senior Security Engineer, AI/ML, National Security, Public Sector

About the role

Our Security team works to create and maintain the safest operating environment for Google's users and developers. Security Engineers work with network equipment and actively monitor our systems for attacks and intrusions. In this role, you will also work with software engineers to proactively identify and fix security flaws and vulnerabilities.

Responsibilities

• Architect and manage LLM deployments across on-premises (NVIDIA/AMD) and cloud (cloud computing platform, Google Cloud platform (GCP)) environments. Audit multi-agent orchestration, agent construction, and vector databases to map data flows and enforce privilege boundaries.
• Use Docker and Kubernetes to orchestrate scalable inference and training environments, optimizing Graphics Processing Unit (GPU) utilization and resource isolation.
• Protect model weights, secure data ingestion, and harden inference endpoints across the Machine Learning operations (MLOps) lifecycle.
• Investigate and mitigate AI-specific threats (e.g., prompt injection, jailbreaking, data poisoning). Map testing findings to MITRE ATLAS, OWASP for LLMs, and STRIDE models.
• Bridge local high-compute clusters and cloud AI services while maintaining a consistent security posture.

Qualifications

• Minimum qualifications:
• - Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field or equivalent practical experience.
• - 5 years of experience in AI/ML development, AI infrastructure engineering, or software development.
• - 5 years of experience with containerization (Docker) and orchestration (Kubernetes).
• - 5 years of experience with Python and with libraries like PyTorch, TensorFlow, or Hugging Face Transformers.
• - Ability to travel up to 25% of the time as needed.
• - Must possess an active Top Secret/SCI security clearance with current polygraph.
• Preferred qualifications:
• - 5 years of experience in AI/ML research or software development.
• - Experience with LLM deployment frameworks such as vLLM, NVIDIA Triton, or Ollama and agent development.
• - Knowledge of open worldwide application security project (OWASP) for LLMs or similar security frameworks.
• - Familiarity with cloud-native AI services (e.g., cloud computing platform, Google Vertex AI).
• - Track record of deploying AI models on air-gapped or on-premises high-performance computing (HPC) systems.

Pay

US: $174,000 - $253,000 (USD) + 15% bonus target + equity + benefits

Schedule

Full-time