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About the role
AI engineer, with GCP Vertex AI , Python & IAM Security
Experienced AI/ML engineer with 10+ years' expertise in GCP Vertex AI, Python, and IAM security to design and deploy AI-driven cloud access governance and automation solutions.
Interview Process: 1 round interview
Location: 100% Remote
Preference to US Citizen, Green Card holder.
Key Responsibilities:
Use Vertex AI to model, detect, and fix misaligned IAM roles and permissions in GCP
Design AI-powered workflows to reduce overprovisioning and enforce least-privilege access
Operationalize AI models to automatically monitor and remediate permission risks across GCP
Collaborate with GCP security engineers and platform teams to integrate solutions within CVS's broader cloud architecture
Contribute to IAM strategy, access control policy improvements, and model governance
Leverage tools like Vertex AI Pipelines, Cloud Functions, and BigQuery for deployment and data analysis
Must Haves:
10+ years of experience in AI/ML engineering or cloud automation roles, with at least 2+ years working in GCP environments
Strong hands-on experience with Vertex AI, including model building, tuning, deployment, and monitoring
Deep familiarity with GCP IAM, roles/permissions structure, and access control policies
Proven experience securing cloud-native environments through AI/ML solutions
Proficiency in Python, with strong experience using ML libraries such as TensorFlow, scikit-learn, or PyTorch
Experience building CI/CD pipelines for ML models, preferably with GCP-native tools
Understanding of cloud security operations, risk detection, and policy enforcement
Nice to Have:
Familiarity with Security Command Center, Policy Intelligence, and GCP's security tooling
Experience with Access Transparency and GCP audit logging
Background in building ML models for security-specific use cases such as access anomaly detection, insider threat, or misconfiguration analysis
Google Cloud Professional certifications (e.g., Professional Machine Learning Engineer, Professional Cloud Security Engineer)
Knowledge of MLOps workflows, governance, and compliance in regulated environments
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