> Markdown version of [/jobs/ext/4029968-enterprise-ai-security-engineer](https://www.wearedevelopers.com/jobs/ext/4029968-enterprise-ai-security-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Enterprise AI Security Engineer - **Company:** Palo Alto Networks - **Location:** United States - **Experience:** Expert - **Salary:** $129,200.0 - $209,000.0 - **Contract:** Permanent contract - **Skills:** Training Data, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software as a Service, Cloud Computing, Cloud Computing Security, Cyber Security, Computer Programming, Computer Engineering, Information Leak Prevention, Identity and Access Management, Python (Programming Language), Open Web Application Security, Systems Integration, Enterprise Data Management, Scripting, Google Cloud, Data Ingestion, Open-source Models, Large Language Models, Software Security, Data Poisoning, AI Coding Agents, Information Technology, Palo Alto Networks, Integration Frameworks, Artificial Intelligence Governance, Api Gateway, Api Management - **Published:** October 30, 2026 - **Apply:** https://startup.jobs/senior-enterprise-ai-security-engineer-paloaltonetworks-com-10620532 ## About the Role * 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. * Demonstrated technical expertise in AI/ML security risks, including prompt injection, model evasion, data poisoning, insecure model supply chains and LLM application vulnerabilities. * Demonstrated Experience in implementing AI guardrails (sensitive data and secrets detection, prompt-injection defenses and tool-call policies) across AI assistants, coding agents and internally built agents. * Proven experience building automated detection and remediation workflows. * Strong practical 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 (e.g., Python, Go) for developing 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 have: Relevant cloud or security certifications (e.g., AWS solutions architect, Google Cloud certified - Associate, CCSP, PCNSE). ## Description Palo Alto Networks protects tens of thousands of people every day from Cyber bad-actors, but who protects Palo Alto Networks? The Palo Alto Networks Enterprise Security team has this incredible responsibility and, as a Senior Enterprise AI Security Engineer, it's your job to protect the team so we can protect the world! As artificial intelligence transforms enterprise operations, you will take the lead in securing AI adoption across our entire organization. In this role, you will join a critical mission, spearheading the discovery and inventory of all enterprise AI usage, uncovering shadow AI tools, models, APIs and third-party integrations. Working closely with our Enterprise Security team, you will architect and deploy automated guardrails and remediation workflows that eliminate risk while empowering business acceleration. Your Impact * Lead the discovery, inventory and visibility efforts for all AI usage across the enterprise, systematically 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 that mitigate AI risks without slowing engineering or business velocity. * Design and deploy threat mitigation controls against AI-specific vulnerabilities, such as direct and indirect prompt injection, jailbreaking, training data poisoning and insecure output handling. * Partner with Enterprise Data Protection team to design context-aware data loss prevention (DLP) controls, preventing unauthorized data ingestion or leakage into AI model pipelines. * Conduct assessments for AI applications, agents, integrations (including MCP servers and tool connectors) and third-party AI products. * Research and implement emerging AI security frameworks and tooling (e.g., OWASP Top 10 for LLMs, MITRE ATLAS, NIST AI RMF). * Collaborate with cloud, infrastructure and application security teams to review, document and harden model hosting environments, AI workloads and API gateways