AI Security Engineer

AspenView Technology Partners

AI Security Engineer at AspenView responsible for establishing security for AI solutions and frameworks. Collaborating with teams to embed security in AI systems and mitigate cyber risks.

Posted 6/24/2026full-timeDenver • Colorado • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AzureCloudCyber Security

About the role

Key responsibilities & impact

Establish and operationalize security controls for emerging Artificial Intelligence and Machine Learning capabilities across the enterprise.
Embed security into AI solution design, protecting AI models and data pipelines, and enabling secure adoption of AI use cases across business and technology functions.
Work closely with Digital, Data, AI, Security Architecture, Engineering, and Cyber Defense Operations teams to define secure AI architecture patterns, implement guardrails, and ensure AI platforms operate within client’s cybersecurity, risk, and governance standards.
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.
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 development of monitoring use cases for AI misuse, abnormal model behavior, unauthorized access, and suspicious data movement.

Requirements

What you’ll need

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.
Experience with Microsoft Azure AI services, OpenAI integrations, Databricks, or enterprise AI platforms preferred.
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 preferred.

Benefits

Comp & perks

Competitive base
Comprehensive benefits and wellness support
Flexible work model: hybrid, remote, or in-office
Real growth opportunities and leadership visibility
Inclusive, respectful culture that blends U.S. innovation with Colombian heart
A company that listens, invests in you, and celebrates wins together

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Hard Skills & Tools

cybersecurity engineeringsecurity architecturecloud securitydata protectionapplication securityAI deployment patternsmachine learningAPI usagedata integrationsecure AI controls

Certifications

CISSPCCSPcloud security certifications