Senior Associate - AI AppSec Engineer Job Details | New York Life Insurance Co

New York Life is hiring a Senior Associate - AI AppSec Engineer to secure AI applications, agentic systems, and supporting platform services across development and production. The role embeds security controls and guardrails throughout the AI lifecycle, partnering with engineering, MLOps, data science, and risk teams, with a primary focus on Google Cloud Vertex AI.

Responsibilities:

• Design and implement application security controls for AI applications, agentic systems, and tool-invoking workflows, ensuring secure-by-default patterns are embedded throughout the software development lifecycle
• Build and operationalize security guardrails that protect against emerging AI threats, including prompt injection, indirect prompt injection, unsafe tool invocation, data exfiltration, model abuse, and other evolving attack techniques
• Integrate AI security controls into existing application security, CI/CD, SSDLC, and infrastructure-as-code processes while helping secure AI platform workflows across data ingestion, model training, deployment, serving, and runtime execution with a primary focus on Google Cloud Vertex AI
• Partner with MLOps platform teams, AI engineers, data scientists, cloud engineering, and Model Risk Management to review identity architectures, automate security controls, remediate findings, and establish reusable security standards across enterprise AI initiatives
• Develop Python-based automation, security tooling, detection capabilities, and technical guidance that improve the organization's ability to securely deploy, monitor, and scale AI solutions in production

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related discipline (or equivalent practical experience) with 5+ years of experience in application security, cloud security, security engineering, or a closely related field
• Hands-on experience securing production AI platforms
• comparable experience with Amazon SageMaker or Azure Machine Learning will also be considered
• Strong understanding of AI application and model lifecycles, including data ingestion, training, model registry, deployment, online and offline serving, and secure environment separation across development, training, staging, and production
• Experience implementing security controls within CI/CD pipelines and infrastructure-as-code environments, along with knowledge of cloud IAM, least-privilege principles, service accounts, workload identity, and non-human identity management
• Knowledge of modern application security practices including authentication and authorization, secure API design, software supply chain security (SLSA, SBOMs, signed artifacts), secrets management, and AI-specific threat models
• Proficiency in Python for automation, security tooling, and detection engineering, with the ability to independently implement, troubleshoot, and evolve security solutions in partnership with cross-functional teams
• experience in Google Cloud Vertex AI