Senior Associate - AI Platform Security Engineer
About The Position
The Security Engineer will play a key role in designing, engineering, and securing NYL’s AI development platform built on Google Cloud and Vertex AI. This is a hands-on security engineering role focused on establishing secure-by-design foundations for AI and ML workloads, including data ingestion, model development, training pipelines, and deployment. The engineer will work closely with cloud platform, data science, and ML engineering teams to implement security controls that protect sensitive data while enabling rapid experimentation and delivery. This role requires deep expertise in cloud security, identity, network controls, and automation, combined with a practical understanding of AI/ML development patterns in regulated environments.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, or equivalent experience.
- 5+ years of experience in cloud security or security engineering roles.
- Hands-on experience securing Google Cloud Platform environments.
- Direct experience with Vertex AI or comparable ML platforms, including securing end-to-end ML workflows.
- Strong knowledge of cloud IAM, least-privilege design, and non-human identity management.
- Experience implementing network security controls in cloud environments (VPCs, private endpoints, service perimeters).
- Familiarity with AI/ML security risks such as data poisoning, model theft, inference abuse, and data leakage.
- Proficiency with Python for security automation and policy enforcement.
- Experience with infrastructure-as-code (Terraform preferred).
- Understanding of regulatory and compliance requirements in financial services environments.
Nice To Haves
- Google Professional Cloud Security Engineer certification.
- Experience securing AI/ML platforms in highly regulated industries.
- Familiarity with AI security frameworks such as MITRE ATLAS.
- Experience with CI/CD integration for ML pipelines and security guardrails.
- Knowledge of confidential computing and secure data processing techniques.
- Exposure to generative AI security concerns (LLMs, RAG, agents).
Responsibilities
- Engineer, configure, and maintain security controls for Google Cloud and Vertex AI environments.
- Design and implement secure Vertex AI architectures covering notebooks, pipelines, model registry, endpoints, and feature stores.
- Define and enforce IAM patterns for human and non-human identities, including service accounts and Workload Identity Federation.
- Implement network security controls such as VPC design, private connectivity, service perimeters, and egress restrictions for AI workloads.
- Engineer encryption strategies for AI data and artifacts, including CMEK, data-at-rest, and data-in-transit protections.
- Establish security guardrails and baseline configurations for AI development teams using infrastructure-as-code.
- Integrate audit logging, monitoring, and alerting for Vertex AI and GCP security events.
- Implement DLP controls to prevent sensitive data exposure during training and inference workflows.
- Conduct threat modeling and security assessments for AI and ML use cases.
- Partner with data science, ML engineering, and cloud platform teams to embed security into development workflows without impeding velocity.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
