AI Infrastructure Security Engineer

C Services L.L.C.
Portland, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Portland, United States of America

Tech stack

Kubernetes Security
API
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cloud Computing
Cloud Computing Security
Data Governance
Identity and Access Management
Key Management
Software Architecture
Software Deployment
AI Infrastructure
Data Logging
Cloud Platform System
Large Language Models
Containerization
Integration Frameworks
Api Design
Automation Anywhere
Devsecops
Docker

Job description

We are building a high-performance AI Red Team to rigorously stress-test and harden enterprise-scale AI systems.

While model security is critical, AI risk often lives in the surrounding infrastructure - data pipelines, APIs, cloud configurations, access controls, and deployment architecture.

We are seeking an AI Infrastructure Security Engineer who can assess, challenge, and strengthen the full AI system stack.

This role ensures our AI products meet the expectations of enterprise and regulated customers.

What You'll Do

  • Review and assess AI deployment architectures across cloud environments
  • Conduct infrastructure-level security testing for:
  • API exposure
  • Authentication & authorization controls
  • Secrets and key management
  • Data encryption in transit and at rest
  • Logging and monitoring configurations
  • Evaluate RAG pipelines, vector databases, and embedding workflows
  • Identify vulnerabilities across:
  • Model hosting environments
  • Containerized deployments
  • CI/CD pipelines
  • Third-party integrations
  • Partner with engineering and security teams to validate remediations
  • Align findings to enterprise security frameworks where applicable
  • Produce structured documentation suitable for internal security and compliance teams

You will ensure AI systems are secure not just in theory, but in practice.

Requirements

Core Technical Experience

  • Strong background in cloud security (AWS, Azure, or GCP)
  • Experience securing API-based systems
  • Knowledge of container security (Docker, Kubernetes)
  • Familiarity with identity and access management models
  • Experience with encryption standards and key management
  • Strong understanding of DevSecOps principles

AI Systems Familiarity

  • Exposure to AI/ML deployment environments
  • Familiarity with:
  • LLM API architectures
  • RAG systems
  • Vector databases
  • Model hosting infrastructure
  • Understanding of data governance within AI workflows

Enterprise Environment Experience

  • Experience working within ISO 27001 or SOC 2 environments
  • Understanding of cloud security control frameworks (ISO 27017 helpful)
  • Ability to communicate findings clearly to both engineering and governance teams

Who You Are

  • Systems-oriented thinker
  • Detail-driven but pragmatic
  • Comfortable challenging architectural decisions
  • Independent and fast-moving
  • Comfortable operating close to executive leadership
  • Enterprise-aware and security-minded

You understand that AI security is only as strong as its weakest infrastructure layer.

Benefits & conditions

  • Comprehensive Private Medical Coverage
  • Support for Mental Health Expenses
  • Life Insurance Options
  • Attractive Compensation Package

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