Job Title: GCP Security Cloud DevOps Engineer / Vertex AI Engineer Remote: U.S.-based required Duration: 6–12 months contract-to-hire Interviews: 3–4 rounds Team: Enterprise Cloud Security – AI Cloud Security Team Summary: We are standing up a new AI-focused team within the Cloud Security group at a nationally recognized enterprise-scale organization. This role is for a hands-on Vertex AI Engineer focused on building scalable ML frameworks in Google Cloud with a direct application in cloud security. You'll be part of a high-performance group working across Azure, GCP, AWS, containers, and applied AI. This is a net-new position with significant influence and opportunity. Scope of Work: • Build, deploy, and manage ML models in Vertex AI • Architect and implement AI-driven security automation across GCP • Create enforcement logic and automated remediation using Python, Terraform, and GitHub Actions • Stand up ML pipelines with Dataflow, Dataproc, BigQuery, and GCP-native tools • Collaborate with cloud security engineers to establish governance rules and codify them in infrastructure • Research and prototype agentic and cognitive AI approaches relevant to threat detection and response • Support deployment in GKE environments with a focus on scalable, secure orchestration Key Technologies: • Vertex AI (required): End-to-end model lifecycle management including development, training, and deployment • GKE: For containerized inference and scalable deployment • BigQuery, Dataflow, Dataproc, Cloud Storage: For training data management and pipeline operations • Python, Terraform, GitHub Actions: For infrastructure and orchestration • ML Frameworks: TensorFlow, PyTorch, scikit-learn, XGBoost Qualifications: • 5+ years of hands-on experience in cloud-native ML engineering • 5+ years working in GCP with deep expertise in Vertex AI • Strong grounding in machine learning model design, training, and operationalization • Proven experience in applying AI/ML within a cloud security context • Expert-level knowledge of Kubernetes / GKE in production environments. • Experience deploying secure AI solutions in enterprise GCP environments • Familiarity with CSPM tools such as Prisma or Wiz is a plus Google Cloud Certifications: • Cloud Digital Leader or above – Required • Associate Cloud Engineer or above – Required • Professional Cloud Architect – Highly Preferred • Professional DevOps Engineer – Highly Preferred Preferred Traits: • Operates like an internal Special-Ops team member—fast, precise, and collaborative • Comfortable in fast-forming teams solving unsolved problems • Capable of applying passion for researching emerging AI security trends into translating them into engineering deliverables Note: Candidates should be comfortable operating under a 1099 model. HIPAA and Security Awareness Training (provided, ~45 mins total) will be required prior to client access.