AI Security Specialist

Ascension•Remote,

2d•$105,830 - $147,521•Remote

About The Position

This role focuses on AI security operations, investigations, secure AI development, and AI security governance. The specialist will evaluate and implement AI security tooling, support investigations of AI security findings and incidents, partner with various teams throughout the AI SDLC to enable secure AI development, and develop AI security guardrails and standards. The position requires assessing AI applications against security frameworks and ensuring compliance with enterprise policies and regulations.

Requirements

High School diploma equivalency with 2 years of cumulative experience OR Associate's degree/Bachelor's degree OR 4 years of applicable cumulative job specific experience required.
5+ years of cybersecurity experience with hands-on expertise in security investigations, incident response, application security, cloud security, or threat detection.
Understanding of large language models (LLMs), AI agents, retrieval-augmented generation (RAG), AI application architectures, and common AI security risks.
Familiarity with secure software development practices, AI development workflows, and CI/CD pipelines.
Experience securing AI solutions in Google Cloud Platform (GCP) and/or Microsoft Azure, including platforms such as Vertex AI or Azure AI Foundry.
Familiarity with AI-assisted development tools, cloud-native security controls, identity and access management, and CI/CD pipelines is preferred.

Nice To Haves

Relevant certifications: CISSP or AI security-focused certifications are preferred.

Responsibilities

Evaluate, implement, and operate AI security tooling to monitor AI use across cloud and endpoint environments, investigate findings, and improve security visibility.
Support investigations of AI security findings and incidents—including over-permissioned agents, sensitive data (e.g., PHI) exposure, and AI application security issues—partnering with Incident Response, engineering, and business teams to assess impact and drive remediation.
Partner with AI engineering, Application Security, DevSecOps, infrastructure, and business teams throughout the AI SDLC to review architectures, validate findings, implement data security controls, and enable secure AI development.
Develop AI security guardrails, standards, technical documentation, and reusable frameworks.
Assess AI applications against security frameworks (e.g., NIST AI RMF, OWASP Top 10 for LLMs) and ensure compliance with enterprise policies, governance requirements, and applicable regulations.