AI engineer

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