Senior AI/ML Security Engineer - On-Prem & Cloud

Google; Maryland; Hybrid; USD 174,000 - 253,000; Full time

Benefits offered by this job

15% bonus target

Equity

Benefits

Job summary

Google Public Sector in the United States seeks a Security Engineer focused on defending AI deployments. You’ll build resilient AI infrastructure, configure security for local on‑prem GPU clusters and cloud environments, and work with cross‑functional teams to identify vulnerabilities.

The role requires deep AI/ML expertise, knowledge of LLMs, and experience with Docker/Kubernetes. Applicants must be onsite in Fort Meade, MD, with the option for remote locations as described, and hold a current

Qualifications

• Bachelor's degree or equivalent practical experience in CS/DS/AI or related field.
• 5 years in AI/ML development, AI infrastructure, or software development.
• 5 years with Docker and Kubernetes.
• 5 years of Python and libraries like PyTorch, TensorFlow, or Hugging Face Transformers.
• Willingness to travel up to 25% and active Top Secret/SCI clearance with polygraph.

Responsibilities

• Architect and manage LLM deployments on‑prem and cloud, audit multi-agent orchestration and data flows.
• Use Docker and Kubernetes to scale inference and training, optimize GPU utilization.
• Protect model weights, secure data ingestion, and harden endpoints across the MLOps lifecycle.
• Investigate and mitigate AI threats; map 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.

Skills

AI/ML development

Security

Adversarial testing

Python

MITRE ATLAS/OWASP knowledge

Education

Bachelor's degree in CS/DS/AI or related field

Tools

Docker

Kubernetes

Cloud platforms

Job description

Google Public Sector in the United States seeks a Security Engineer focused on defending AI deployments. You’ll build resilient AI infrastructure, configure security for local on‑prem GPU clusters and cloud environments, and work with cross‑functional teams to identify vulnerabilities.

The role requires deep AI/ML expertise, knowledge of LLMs, and experience with Docker/Kubernetes. Applicants must be onsite in Fort Meade, MD, with the option for remote locations as described, and hold a current