Senior Enterprise AI Security Engineer

Palo Alto Networks

Santa Clara (CA)

On-site

USD 129,000 - 209,000

Full time

4 days ago

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Benefits offered by this job

Onsite in Santa Clara

Stock options possible

Job summary

Cybersecurity Jobs in Santa Clara, CA, is seeking an experienced security engineer to build enterprise-grade AI security controls. You will lead discovery, guardrails, and policy enforcement to mitigate AI risks while preserving engineering velocity.

Collaborating with data protection, cloud, and app security teams, you will harden hosting environments, AI workloads, and API gateways. Onsite role with competitive USD salary and RSU/bonus potential.

Qualifications

5+ years of hands-on enterprise security engineering experience.
Proven expertise in AI/ML security risks and defenses.
Experience implementing AI guardrails and policy enforcement.
Experience building automated detection and remediation workflows.
Strong knowledge of IAM, Cloud Infrastructure, endpoint security, and DLP.

Responsibilities

Lead discovery, inventory, and visibility for enterprise AI usage.
Architect automated remediation workflows and policy enforcement.
Design and deploy threat mitigation controls for AI vulnerabilities.
Collaborate with Enterprise Data Protection on context-aware DLP.
Assess AI apps and integrations, including MCP servers and tools.
Research and implement emerging AI security frameworks and tooling.
Collaborate with cloud, infra, and app security to harden hosting environments and API gateways.

Skills

Python

Security engineering

Cloud security

AI/ML security

Threat modeling

Education

Bachelor's or Master's degree in CS/CE/Cybersecurity

Tools

AWS

GCP

Azure

MCP

OWASP Top 10 for LLMs

MITRE ATLAS

NIST AI RMF

Job description

Build enterprise-grade security controls for AI adoption across the organization.

Responsibilities

Lead discovery, inventory, and visibility for enterprise AI usage, tracking approved AI systems, third-party SaaS tools, open-source models, developer plugins, and shadow AI integrations.
Architect, build, and maintain automated remediation workflows and policy enforcement engines to mitigate AI risks without reducing engineering or business velocity.
Design and deploy threat mitigation controls for AI-specific vulnerabilities, including direct and indirect prompt injection, jailbreaking, training data poisoning, and insecure output handling.
Partner with the Enterprise Data Protection team to design context-aware DLP controls that prevent unauthorized data ingestion or leakage into AI model pipelines.
Assess AI applications, agents, and integrations, including MCP servers and tool connectors, plus third-party AI products.
Research and implement emerging AI security frameworks and tooling, such as OWASP Top 10 for LLMs, MITRE ATLAS, and NIST AI RMF.
Collaborate with cloud, infrastructure, and application security teams to review, document, and harden model hosting environments, AI workloads, and API gateways.

Requirements

Bachelor's or Master's degree in Computer Science, Computer Engineering, Cybersecurity, or a related STEM field, or equivalent practical experience.
5+ years of hands-on experience in enterprise security engineering, application security, cloud security, or security architecture.
Proven expertise in AI/ML security risks, including prompt injection, model evasion, data poisoning, insecure model supply chains, and LLM application vulnerabilities.
Experience implementing AI guardrails, including sensitive data and secrets detection, prompt-injection defenses, and tool-call policies across AI assistants, coding agents, and internally built agents.
Experience building automated detection and remediation workflows.
Strong knowledge of core enterprise security domains: Identity & Access Management, Cloud Infrastructure (AWS, GCP, or Azure), endpoint security, and Data Protection/DLP.
Proficiency in at least one modern programming or scripting language, such as Python or Go, for automation, API integrations, and custom security tooling.
Strong communication and cross-functional leadership skills, with a track record of enabling business and engineering teams to adopt new technologies safely.