AI Security Engineer

Role Summary\n\nThe AI Security Engineer is responsible for securing the enablement and use of AI, GenAI, LLM, and agentic technologies across the enterprise, balancing business velocity with protection of Applied Materials\u2019 intellectual property, sensitive data, and customer trust.\n\nThis role drives AI security governance, risk management, technical guardrails, and operational oversight for AI systems and AI\u2011integrated applications across the full lifecycle\u2014from intake and design through deployment, monitoring, and incident response. The role serves as a key focal point for AI security execution in the US and partners closely with global counterparts and cross\u2011pillar security teams to deliver scalable, measurable, and auditable AI security controls.\n\nKey Responsibilities\n\nTechnical Mindset \u0026 Operating Style\n\n * Highly technology\u2011savvy and continuously current on rapidly evolving AI/LLM platforms, agent frameworks, developer tooling, and emerging attack techniques through hands\u2011on experimentation and learning.\n * Brings strong engineering intuition through prior software development experience or equivalent hands\u2011on technical background, enabling effective architecture reviews, threat modeling, and pragmatic security guidance.\n * Comfortable reading, writing, and reviewing code (e.g., Python, TypeScript, or similar) to understand AI workflows, model integrations, APIs, pipelines, and real\u2011world failure modes.\n * Practical experience experimenting with AI tooling, copilots, agents, and \u201cvibe\u2011coding\u201d workflows, with an understanding of how developers\u2019 prototype, iterate, and ship AI\u2011enabled systems.\n * Able to translate modern developer behaviors (prompt\u2011driven development, agent orchestration, rapid iteration) into realistic, enforceable security controls rather than theoretical policy.\n * Uses technical credibility to influence engineering teams, accelerate adoption of secure AI patterns, and ensure security enables\u2014rather than blocks\u2014innovation.\n\n\n\nAI Security Governance \u0026 Intake\n\n * Own enterprise AI discovery, inventory, and intake workflows covering AI use cases, models, tools, agents, and integrations\n * Define and enforce AI risk tiering and classification (data sensitivity, model risk, autonomy level, exposure)\n * Partner with AI Governance, Legal, Privacy, and Risk teams to establish approval, exception, and waiver processes\n * Ensure AI security controls align with enterprise risk management and audit expectations\n\n\n\nAI Threat Modeling \u0026 Risk Management\n\n * Lead AI\u2011specific threat modeling, including prompt injection, data leakage, model poisoning, tool abuse, agentic risk, and supply\u2011chain threats\n * Define secure AI architecture patterns and prohibited design patterns\n * Conduct and oversee risk assessments for LLM\u2011integrated applications, internal copilots, and external AI services\n * Track AI security risks and exceptions through remediation and closure\n\n\n\nTechnical Controls \u0026 Guardrails\n\n * Define and operationalize AI security guardrails, including:\n * Authentication and authorization for AI systems\n * Data boundaries, retention, and usage controls\n * Output/content controls and policy enforcement\n * Identity, secrets, and key management for AI workloads\n * Lead security requirements for agent frameworks, MCP servers/clients, AI gateways, and proxies\n * Partner with AppSec and Platform teams to deliver secure \u201cpaved\u2011road\u201d AI solutions for engineering teams\n\n\n\nSecure AI Lifecycle, Testing \u0026 Monitoring\n\n * Establish secure AI lifecycle gates (pre\u2011prod, prod, post\u2011deployment)\n * Own AI security testing and validation, including red teaming, abuse testing, and guardrail effectiveness\n * Define requirements for telemetry, audit logging, and retention for AI sessions, tool calls, and memory usage\n * Integrate AI signals into SIEM, detection, and incident response workflows\n\n\n\nIncident Response \u0026 Continuous Improvement\n\n * Own AI\u2011specific detection use cases and alerting strategies\n * Partner with IR teams to develop and maintain AI incident response posture and integration with SIEM tools\n * Lead post\u2011incident reviews and drive control improvements\n * Publish executive and operational AI security metrics and dashboards\n\n\n\nRequired Qualifications\n\n * 10+ years in security architecture, application security, cloud/platform security, or related fields\n * Demonstrated experience securing AI/ML or LLM\u2011based systems in enterprise environments\n * Strong background in threat modeling, secure design, and risk management\n * Experience working cross\u2011functionally with engineering, product, legal, and compliance teams\n * Strong written and verbal communication skills, including executive\u2011level communication\n\n\n\nPreferred Qualifications\n\n * Prior experience as a software engineer, platform engineer, or security engineer with significant coding responsibilities\n * Experience with AI governance frameworks or enterprise risk management programs\n * Familiarity with security testing, red teaming, and detection engineering\n * Experience building security programs with clear KPIs, metrics, and audit readiness\n\n\n\n## Qualifications\n\n### Education:\n\nBachelor\u0027s Degree\n\n### Skills\n\nAI Security Governance, Generative AI, IT System Security, JFrog, Large Language Model (LLM) Fine-Tuning, Platform Security, Qualys Vulnerability Management\n\n### Certifications:\n\n### Languages:\n\n### Years of Experience:\n\n7 - 10 Years\n\n### Work Experience:\n\n## Additional Information\n\n### \n\n### Shift:\n\n10-Day 8-Hr (United States of America)\n\n### \n\n### Travel:\n\nNo\n\n### \n\n### Relocation Eligible:\n\nNo\n\n### Referral Payment Plan:\n\nEmployee Referral (Standard)\n\nU.S. Salary Range:\n\n$108,000.00 - $148,500.00\n\nThe salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable. \n\nFor all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.\n\nApplied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law. \n