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# Cloud Security Engineering Specialist

- **Company:** Ascension
- **Location:** St. Louis, MO, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing, Cloud Computing Security, Cloud Engineering, Cyber Security, Continuous Integration, Identity and Access Management, Intrusion Detection and Prevention, Open Web Application Security, Systems Development Life Cycle, Software Engineering, Data Logging, Google Cloud, Large Language Models, Kubernetes, Terraform, Prisma Cloud Platform, Oracle Cloud Infrastructure, Security Orchestration, Automation & Response
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/cloud-security-engineering-specialist-saint-louis-mo--d11a3aee-b69f-49c4-bd4d-64124554c168

## About the Role

Cloud Computing, Software Engineering, Cloud Computing, Software Engineering, Continuous Improvement, GCP (Good Clinical Practices), Security Architecture, Microsoft Windows Azure, Cloud Architecture, Security Design, * High School diploma equivalency with 2 years of cumulative experience OR Associate''s degree/Bachelor''s degree OR 4 years of applicable cumulative job specific experience required., * Cloud Security & CNAPP Technical Expertise: 5+ years of hands-on experience engineering, securing, and operating enterprise cloud environments across Azure, GCP, or OCIâincluding deep technical expertise in cloud networking, IAM, Kubernetes/containers, Infrastructure as Code (Terraform), CI/CD security, and cloud logging. Requires proven experience deploying and managing leading CNAPP platforms (such as Wiz, Prisma Cloud, Orca, Defender for Cloud, or Upwind); relevant certifications like CCSP or CISSP are preferred.

 * AI Workload Security & Governance: Advanced understanding of modern AI security concepts, including the OWASP Top 10 for LLM Applications, AI-specific threat vectors and risks, secure AI SDLC practices, and governance frameworks for enterprise AI workloads.

## Description

* Cloud Security Engineering: Design, implement, and continuously improve security across enterprise multi-cloud environments (Azure, GCP, and OCI) by developing secure landing zones, cloud security architectures, identity controls, Infrastructure as Code (Terraform) guardrails, and Kubernetes/container security capabilities.
 * CNAPP & Cloud Risk Management: Engineer and optimize Cloud-Native Application Protection Platform (CNAPP) capabilities. Drive vulnerability prioritization, remediation strategies, configuration drift detection, and continuous compliance across cloud environments.
 * Threat Detection & Security Automation: Develop automated security controls, policy enforcement, and remediation workflows to improve cloud visibility, operational efficiency, and secure-by-default deployments.
 * AI Security & Governance: Partner with AI Security, AI Engineering, and Cloud Engineering teams to assess AI technologies and workloads, prioritize and mitigate AI-related risks, develop cloud and AI security standards and technical controls, and support the secure AI development lifecycle (AI SDLC).
 * Technical Leadership & Security Standards: Develop cloud security standards, perform design reviews and threat modeling, evaluate emerging technologies, and mentor team members through technical guidance, knowledge sharing, and hands-on coaching.