Security Engineer AI
United States of America
Full Time
4 hours ago
$105,000 - $130,000 USD
No H1B
Key skills
Security EngineeringCloud SecurityInfrastructure SecurityAWSAzureOffice 365Microsoft CopilotEnterprise AI ToolsIdentityAccess ManagementRole Based Access Control (RBAC)Conditional AccessMulti-Factor Authentication (MFA)Security MonitoringData Loss Prevention (DLP)Information ClassificationAI Risk ManagementSecurity Tooling - Microsoft Entra IDSecurity Tooling - Microsoft PurviewAI SecurityCloud AI InfrastructureAILarge Language ModelsClaudeRAGEntra IDSaaSRisk ManagementOWASP
About this role
Best Friends Animal Society is seeking a Security Engineer AI to implement and operate security controls across enterprise cloud platforms, SaaS applications, and AI-enabled tools. The role focuses on AI security and Cloud AI infrastructure, ensuring secure usage of AI and cloud technologies in accordance with enterprise security standards.
Responsibilities:
- Implement and maintain security controls for enterprise AI tools, including Microsoft Copilot and other AI-enabled SaaS platforms
- Support the secure onboarding, configuration, and monitoring of AI features and other enterprise SaaS platforms
- Enforce data access boundaries and usage restrictions for AI tools based on data classification and identity
- Assist in reviewing custom AI use cases and integrations for security risks, including data exposure through prompts or outputs, improper access to sensitive information, and misuse of AI-driven automation
- Design, review, and enforce security controls for enterprise AI platforms, including productivity copilots, internal large language models (LLMs), and third-party AI services
- Partner with security engineering and cloud teams to secure AI infrastructure
- Participate in architecture and security design reviews for AI-enabled systems prior to production deployment, ensuring appropriate guardrails for data exposure
- Support secure configuration for AI agent usage and implement monitoring and audit logging for AI interactions and tool usage
- Design and implement security controls for AI systems leveraging the Model Context Protocol (MCP)
- Enforce least-privilege access for AI agents interacting with tools, APIs, and data sources
- Secure AI data flows, including retrieval-augmented generation (RAG) pipelines
- Expand logging and monitoring for AI platforms, cloud environments, and SaaS activity
- Participate in incident response efforts by investigating security alerts and supporting response to incidents involving cloud, SaaS, and AI tools
- Assist in developing and maintaining runbooks and response procedures for platform-related incidents
- Partner with engineering teams to embed security into AI platform architectures
- Support and assist with security reviews of cloud-hosted applications and services and overall application security
- Support identity and access management controls across Cloud platforms, SaaS applications, AI tools and integrations
- Implement and maintain, Role based access controls (RBAC), Least privilege access models, Conditional access and MFA policies
- Assist with access reviews and security remediation efforts
- Contribute to the development and maintenance of security standards and technical guidelines. Providing security input to IT, Cloud, and Application teams during solution design and implementation
- Document configurations, processes, and operational procedures related to security controls
- Provide practical, security focused guidance to engineering, IT, and business teams on safe AI usage
Requirements:
- 4-6 years of experience in security engineering, cloud security, or infrastructure security
- 3-4 years hands-on experience with cloud platforms such as AWS, Azure and Office 365
- Experience integrating security monitoring with observability data to detect misuse, data exfiltration, prompt injection, and adversarial AI behaviors
- Working knowledge of identity and access management concepts and controls
- Familiarity with AI enabled tools, platforms and their associated security considerations
- Experience with Microsoft security tooling (e.g., Entra ID, Purview)
- Experience with Microsoft Copilot or other enterprise AI tools
- Experience with data protection, DLP, and information classification
- Experience securing enterprise AI platforms (e.g., Microsoft Copilot, ChatGPT Enterprise, Claude, and internal LLMs)
- Experience in AI risk management initiatives that provide observability data to ensure compliance and safe usage of AI systems
- Familiarity with AI related risk frameworks (e.g., OWASP Top 10 for LLMs, NIST AI Risk Management Framework)