Architect and manage large language model (LLM) deployments across on-premises NVIDIA/AMD hardware and cloud platforms.
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, optimize GPU utilization, and ensure resource isolation.
Protect model weights, secure data ingestion, and harden inference endpoints across the ML operations (MLOps) lifecycle.
Investigate and mitigate AI-specific threats (prompt injection, jailbreaking, data poisoning) and map testing findings to MITRE ATLAS, OWASP for LLMs, and STRIDE models.

Key requirements

Architect and manage large language model (LLM) deployments across on-premises NVIDIA/AMD hardware and cloud platforms.
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, optimize GPU utilization, and ensure resource isolation.
Protect model weights, secure data ingestion, and harden inference endpoints across the ML operations (MLOps) lifecycle.
Investigate and mitigate AI-specific threats (prompt injection, jailbreaking, data poisoning) and map testing findings to MITRE ATLAS, OWASP for LLMs, and STRIDE models.

Jobs at Google

192 active roles from this employer in the JobMatcher catalog.

All company jobs

Jobs at Google

192 active roles from this employer in the JobMatcher catalog.

All company jobs

About the role

Senior Security Engineer, AI/ML for National Security and the Public Sector

Our Security team works to create and maintain the safest operating environment for Google's users and developers. This role focuses on building and defending AI infrastructures, ensuring secure AI deployments from on-prem GPU clusters to cloud-native environments, and protecting against adversarial manipulation.

Responsibilities

Qualifications:

Architect and manage large language model (LLM) deployments across on-premises NVIDIA/AMD hardware and cloud platforms.
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, optimize GPU utilization, and ensure resource isolation.
Protect model weights, secure data ingestion, and harden inference endpoints across the ML operations (MLOps) lifecycle.
Investigate and mitigate AI-specific threats (prompt injection, jailbreaking, data poisoning) and 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.
Bachelor's degree in Computer Science, Data Science, AI, or a related field.
At least 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 libraries such as PyTorch, TensorFlow, or Hugging Face T

About the role

Senior Security Engineer, AI/ML for National Security and the Public Sector

Our Security team works to create and maintain the safest operating environment for Google's users and developers. This role focuses on building and defending AI infrastructures, ensuring secure AI deployments from on-prem GPU clusters to cloud-native environments, and protecting against adversarial manipulation.

Responsibilities

Qualifications:

Architect and manage large language model (LLM) deployments across on-premises NVIDIA/AMD hardware and cloud platforms.
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, optimize GPU utilization, and ensure resource isolation.
Protect model weights, secure data ingestion, and harden inference endpoints across the ML operations (MLOps) lifecycle.
Investigate and mitigate AI-specific threats (prompt injection, jailbreaking, data poisoning) and 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.
Bachelor's degree in Computer Science, Data Science, AI, or a related field.
At least 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 libraries such as PyTorch, TensorFlow, or Hugging Face T

Track similar jobs

Get email alerts when new roles like this are posted.

Based on: Senior Security Engineer, AI/ML