Global Cloud & AI Security Architect

KLA•Ann Arbor, MI

32d•$111,100 - $162,967•Onsite

About The Position

In this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise. The Cloud & AI Security Architect will define and implement security strategies for enterprise cloud, Generative AI, and AI applications. This role will work closely with Cloud, AI/ML, Engineering, Data, and Cybersecurity teams to ensure new cloud and AI technologies are secure by design.

Requirements

8+ years of experience in cybersecurity, cloud security, security architecture, or related areas.
Strong experience with cloud security architecture across AWS, Azure, or GCP.
Strong understanding of Generative AI, LLMs, AI agents, RAG, APIs, and AI security risks.
Experience securing cloud-native technologies including containers, Kubernetes, and microservices.
Strong knowledge of IAM, Zero Trust, network security, data protection, and DLP.
Experience with DevSecOps and Infrastructure-as-Code security.
Ability to evaluate new AI and cloud technologies and translate risks into practical security controls.
Strong communication, presentation, and cross-functional collaboration skills.

Nice To Haves

Experience with AI Security / CNAPP / CSPM / CWPP / CIEM / DSPM / DLP technologies.
Knowledge of OWASP Top 10 for LLM Applications and MITRE ATLAS.
Experience with AI security platforms and enterprise AI governance.
Experience with security automation and Python/API-based integrations.
CISSP, CCSP, cloud security, or AI security certifications are a plus.

Responsibilities

Define security architecture for Generative AI, LLMs, AI agents, copilots, and AI applications.
Identify and mitigate AI risks including prompt injection, data leakage, unauthorized access, insecure AI agents, and excessive permissions.
Develop security controls for AI platforms, RAG, vector databases, APIs, and AI tools.
Establish security standards for enterprise use of ChatGPT, Microsoft Copilot, Claude, and other AI platforms.
Secure AI agents and their access to applications, data, APIs, and enterprise tools.
Evaluate AI security solutions and emerging technologies through POCs and architecture assessments.
Develop an AI Security roadmap and governance framework.
Define security architecture for AWS, Azure, and/or GCP environments.
Secure cloud workloads, applications, containers, Kubernetes, APIs, and serverless services.
Define security controls for identity, access management, network security, data protection, encryption, and logging.
Implement Zero Trust and least-privilege principles across cloud environments.
Partner with Cloud and DevOps teams to integrate security into CI/CD and Infrastructure-as-Code.
Identify cloud security gaps and provide practical remediation plans.
Create cloud and AI security standards, reference architectures, and security patterns.
Perform threat modeling and security assessments for new AI and cloud solutions.
Work with engineering teams to embed security-by-design into technology initiatives.
Evaluate security products, vendors, and emerging technologies.
Develop and maintain the Cloud & AI Security roadmap.
Communicate security risks and recommendations to technical teams and senior leadership.