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Senior AI Engineer GCP Vertex AI
Job in
Boston, Suffolk County, Massachusetts, 02115, USA
Listed on 2026-06-03
Listing for:
3B Staffing
Full Time
position Listed on 2026-06-03
Job specializations:
-
IT/Tech
AI Engineer, Cybersecurity
Job Description & How to Apply Below
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 over provisioning 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 Big Query for deployment and data analysis
- 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 Tensor Flow, scikit-learn, or Py Torch
- Experience building CI/CD pipelines for ML models, preferably with GCP-native tools
- Understanding of cloud security operations, risk detection, and policy enforcement
- 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
Position Requirements
10+ Years
work experience
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