AI Security Engineer

AspenView Technology Partners is focused on transforming organizations through technology by creating high-performing IT teams. The AI Security Engineer will establish and operationalize security controls for AI and machine learning capabilities, ensuring secure architecture patterns and governance practices are in place across the enterprise.

Responsibilities:

• Define secure architecture patterns for AI and machine learning solutions, ensuring protection of models, training pipelines, inference environments, and supporting data flows
• Establish secure integration patterns for AI services across enterprise applications, APIs, cloud platforms, and data environments
• Review AI solution designs to ensure alignment with enterprise security architecture standards and secure-by-design principles
• Support implementation of secure controls across AI development, testing, deployment, and production environments
• Identify, assess, and mitigate AI-specific threats including model poisoning, prompt injection, adversarial attacks, unauthorized model access, data leakage, and misuse of AI outputs
• Define and implement security guardrails for AI model access, API usage, prompt controls, and secure interaction with enterprise data sources
• Establish controls to protect sensitive training data, embeddings, prompts, and inference outputs across AI workflows
• Support validation of third-party AI services and external model integrations from a cybersecurity risk perspective
• Establish AI security standards, engineering guardrails, and governance practices aligned with regulatory requirements, enterprise risk expectations, and responsible AI principles
• Partner with Digital and AI teams to enable secure AI use cases where security accelerates responsible business adoption rather than acts as a blocker
• Support creation of AI security review checkpoints for new AI initiatives, pilots, and production deployments
• Contribute to enterprise AI security policies, reference architectures, and operational standards
• Collaborate with Cyber Defense Operations to operationalize AI-related detection, monitoring, and response capabilities
• Support development of monitoring use cases for AI misuse, abnormal model behavior, unauthorized access, and suspicious data movement
• Define logging and telemetry requirements for AI platforms to improve visibility and incident readiness
• Support integration of AI platform telemetry into enterprise detection and monitoring tools where applicable
• Work closely with Security Architecture, Cloud Engineering, Data teams, Application teams, and AI program owners to ensure consistent security adoption
• Support security reviews for AI vendors, AI-enabled SaaS platforms, and internally developed AI capabilities
• Provide technical guidance to project teams on secure AI implementation and operational controls

Requirements:

• 5–8 years of cybersecurity engineering or security architecture experience, with exposure to cloud security, data protection, or application security
• Experience working with enterprise AI, machine learning, analytics platforms, or data-driven technology environments
• Practical understanding of AI/ML deployment patterns, APIs, model lifecycle, and enterprise data integration
• Clear visibility into AI-related cyber risks and mitigation actions and ability to translate emerging AI risks into practical engineering controls
• Practical AI guardrails established for data, model access, and operational use
• Strong alignment between AI innovation, enterprise security, and regulatory expectations
• Strong understanding of cybersecurity controls across cloud, applications, APIs, identity, and data protection
• Familiarity with AI/ML risks including prompt injection, model abuse, data leakage, and adversarial techniques
• Knowledge of secure architecture principles for modern digital and AI platforms
• Experience with Microsoft Azure AI services, OpenAI integrations, Databricks, or enterprise AI platforms
• Familiarity with emerging AI governance frameworks and responsible AI standards
• Experience with Secure AI controls embedded into enterprise AI initiatives without slowing adoption
• Security certifications such as CISSP, CCSP, or cloud security certifications