Senior Enterprise AI Security Engineer

Palo Alto Networks•Office - USA - CA - Headquarters, CA

1d•$129,200 - $209,000•Onsite

About The Position

As a Senior Enterprise AI Security Engineer on Palo Alto Networks’ Enterprise Security team, you will help secure the company’s adoption of artificial intelligence across the organization. The role focuses on discovering and inventorying enterprise AI usage, including approved systems, third-party SaaS tools, open-source models, developer plugins, APIs, and shadow AI integrations. You will build automated guardrails and remediation workflows that mitigate risk while enabling business and engineering teams to work effectively. You will assess AI applications, agents, integrations, and third-party AI products; design controls against AI-specific threats; and partner with data protection, cloud, infrastructure, and application security teams. The position also involves researching and applying AI security frameworks and strengthening model-hosting environments, AI workloads, and API gateways. Palo Alto Networks states that most teams work from the office full time, with flexibility when needed.

Requirements

Bachelor’s or master’s degree in Computer Science, Computer Engineering, Cybersecurity, or a related STEM field, or equivalent practical experience.
At least 5 years of hands-on experience in enterprise security engineering, application security, cloud security, or security architecture.
Technical 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.
Practical knowledge of enterprise security domains including 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.

Nice To Haves

Relevant cloud or security certifications, such as AWS Solutions Architect, Google Cloud Certified Associate, CCSP, or PCNSE.

Responsibilities

Lead discovery, inventory, and visibility efforts for enterprise AI usage, tracking approved 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 slowing business or engineering work.
Design and deploy threat mitigation controls against 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, integrations—including MCP servers and tool connectors—and 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.