AI Security Engineer

** Who We Are*
* Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips - the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world - like AI and IoT.

If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.

** What We Offer*
* Salary:

$ - $

Location:

Austin,TX, Santa Clara,CA

You'll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible-while learning every day in a supportive leading global company. Visit our Careers website to learn more.

At Applied Materials, we care about the health and wellbeing of our employees. We're committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits () .

** Role Summary*
* The 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' intellectual property, sensitive data, and customer trust.

This role drives AI security governance, risk management, technical guardrails, and operational oversight for AI systems and AI‑integrated applications across the full lifecycle-from 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‑pillar security teams to deliver scalable, measurable, and auditable AI security controls.

** Key Responsibilities*
* ** Technical Mindset & Operating Style*
* + Highly technology‑savvy and continuously current on rapidly evolving AI/LLM platforms, agent frameworks, developer tooling, and emerging attack techniques through hands‑on experimentation and learning.

+ Brings strong engineering intuition through prior software development experience or equivalent hands‑on technical background, enabling effective architecture reviews, threat modeling, and pragmatic security guidance.

+ Comfortable reading, writing, and reviewing code (e.g., Python, Type Script, or similar) to understand AI workflows, model integrations, APIs, pipelines, and real‑world failure modes.

+ Practical experience experimenting with AI tooling, copilots, agents, and "vibe‑coding" workflows, with an understanding of how developers' prototype, iterate, and ship AI‑enabled systems.

+ Able to translate modern developer behaviors (prompt‑driven development, agent orchestration, rapid iteration) into realistic, enforceable security controls rather than theoretical policy.

+ Uses technical credibility to influence engineering teams, accelerate adoption of secure AI patterns, and ensure security enables-rather than blocks-innovation.

** AI Security Governance & Intake*
* + Own enterprise AI discovery, inventory, and intake workflows covering AI use cases, models, tools, agents, and integrations

+ Define and enforce AI risk tiering and classification (data sensitivity, model risk, autonomy level, exposure)

+ Partner with AI Governance, Legal, Privacy, and Risk teams to establish approval, exception, and waiver processes

+ Ensure AI security controls align with enterprise risk management and audit expectations

** AI Threat Modeling & Risk Management*
* + Lead AI‑specific threat modeling, including prompt injection, data leakage, model poisoning, tool abuse, agentic risk, and supply‑chain threats

+ Define secure AI architecture patterns and prohibited design patterns

+ Conduct and oversee risk assessments for LLM‑integrated applications, internal copilots, and external AI services

+…