出海雷达

高级云安全工程师

Senior Cloud Security Engineer

AI开发工程限定地区(需当地身份)
公司Med-Metrix
薪资未公开
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间10 天前
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

职位职责 高级云安全工程师将设计、实施和维护跨我们多云环境的安全控制措施,特别关注于保护AI/ML工作负载并利用AI驱动的安全工具。高级云安全工程师将作为技术领导者,与工程、应用开发和DevOps团队合作,将安全嵌入到云和AI开发的每个阶段中。
职责与任务

  • 在AWS和Azure上设计和实现安全的云架构,包括身份管理、网络安全、加密和密钥管理
  • 实施云原生的日志记录、监控和威胁检测,以提高可见性和事件响应能力
  • 构建基础设施即代码(Terraform、CloudFormation、Bicep)、政策即代码和自动化合规控制
  • 实施和增强云安全态势管理(CSPM)、云工作负载保护(CWPP)和CNAPP功能
  • 对云服务和应用程序进行威胁建模、安全架构审查和风险评估
  • 设计和保护AI/ML环境,包括MLOps流水线、模型安全、推理端点和AI治理
  • 评估和缓解AI特定的威胁,包括提示注入、模型中毒、对抗性攻击和数据泄露
  • 与工程和数据科学团队合作,为受监管数据实施安全设计和隐私保护控制
  • 开发自动化检测、SOAR剧本和AI驱动的威胁狩猎能力
  • 领导对云和AI安全事件的技术响应,包括取证分析和修复
  • 设计和实施符合HIPAA、HITRUST、PCI DSS、SOC 2、NIST CSF和NIST AI RMF要求的安全控制
  • 支持安全审计和合规评估的技术准备、证据收集和修复活动
  • 制定和维护云安全标准、技术指南和AI治理文档
  • 支持企业风险管理及供应商安全评估
  • 在DevSecOps生命周期中集成安全,包括应用、容器和秘密管理
  • 开发安全指标,向相关方沟通技术风险,并推荐持续的安全改进
  • 指导初级工程师,并在工程团队中推广安全最佳实践
  • 其他指派的任务
  • 使用、保护和披露患者的受保护健康信息
查看英文原文

Job Purpose The Senior Cloud Security Engineer will design, implement, and maintain security controls across our multi-cloud environment, with a particular emphasis on securing AI/ML workloads and leveraging AI-driven security tooling. The Senior Cloud Security Engineer will serve as a technical leader, partnering with engineering, application development, and DevOps teams to embed security into every stage of the cloud and AI development lifecycle.
Duties & Responsibilities

  • Design and implement secure cloud architecture across AWS and Azure, including identity, network security, encryption, and key management
  • Implement cloud-native logging, monitoring, and threat detection to improve visibility and incident response
  • Build Infrastructure-as-Code (Terraform, CloudFormation, Bicep), Policy-as-Code, and automated compliance controls
  • Implement and enhance Cloud Security Posture Management (CSPM), Cloud Workload Protection (CWPP), and CNAPP capabilities
  • Conduct threat modeling, security architecture reviews, and risk assessments for cloud services and applications
  • Design and secure AI/ML environments, including MLOps pipelines, model security, inference endpoints, and AI governance
  • Assess and mitigate AI-specific threats, including prompt injection, model poisoning, adversarial attacks, and data leakage
  • Partner with engineering and data science teams to implement secure-by-design and privacy-preserving controls for regulated data
  • Develop automated detections, SOAR playbooks, and AI-driven threat hunting capabilities
  • Lead technical response to cloud and AI security incidents, including forensic analysis and remediation
  • Design and implement security controls supporting HIPAA, HITRUST, PCI DSS, SOC 2, NIST CSF, and NIST AI RMF requirements
  • Support technical readiness, evidence collection, and remediation activities for security audits and compliance assessments
  • Develop and maintain cloud security standards, technical guidance, and AI governance documentation
  • Support enterprise risk management and vendor security assessments
  • Integrate security throughout the DevSecOps lifecycle, including application, container, and secrets management
  • Develop security metrics, communicate technical risks to stakeholders, and recommend continuous security improvements
  • Mentor junior engineers and champion security best practices across engineering teams
  • Other duties as assigned
  • Use, protect and disclose patients’ protected health information (PHI) only in accordance with Health Insurance Portability and Accountability Act (HIPAA) standards
  • Understand and comply with Information Security and HIPAA policies and procedures at all times
  • Limit viewing of PHI to the absolute minimum as necessary to perform assigned duties

Qualifications

  • High school diploma or equivalent required
  • 6+ years of experience in information security, with at least 4 years focused on cloud security engineering
  • Deep hands-on expertise in both AWS and Microsoft Azure, including native security services (e.g., AWS GuardDuty, Security Hub, IAM Identity Center; Microsoft Defender for Cloud, Sentinel, Entra ID)
  • Strong knowledge of IAM, zero trust architecture, network security, encryption, and secrets management in cloud environments
  • Practical experience securing AI/ML systems or LLM-based applications, or demonstrable working knowledge of AI security frameworks (OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF)
  • Proficiency in at least one scripting/programming language (Python preferred) and infrastructure-as-code tooling
  • Experience with container and orchestration security (Docker, Kubernetes, EKS/AKS)
  • Solid understanding of DevSecOps practices and CI/CD security integration
  • Hands-on experience supporting compliance programs such as HIPAA, HITRUST CSF, PCI DSS, and SOC 2 in cloud environments, including audit evidence and control implementation
  • Proficiency in Microsoft Office Suite
  • Strong interpersonal skills, ability to communicate well at all levels of the organization
  • Strong problem solving and creative skills and the ability to exercise sound judgment and make decisions based on accurate and timely analyses
  • High level of integrity and dependability with a strong sense of urgency and results oriented
  • Excellent written and verbal communication skills required

Preferred Qualifications

  • Experience with Google Cloud Platform (GCP) in addition to AWS and Azure
  • Experience deploying or securing MLOps platforms (SageMaker, Vertex AI, Azure ML, Databricks, Kubeflow)
  • Familiarity with AI-driven security platforms and building custom detections using ML techniques
  • Relevant certifications such as CISSP, CCSP, HCISPP, CCSFP (HITRUST), AWS Security Specialty, Azure Security Engineer (AZ-500), GCP Professional Cloud Security Engineer, or GIAC certifications
  • Prior experience in healthcare, health tech, or revenue cycle management environments handling PHI at scale
  • Experience with red teaming or adversarial testing of AI systems
  • Knowledge of data privacy regulations as they apply to AI training data and model outputs, particularly de-identification standards under HIPAA (Safe Harbor and Expert Determination)
  • Contributions to security communities, open-source tooling, or published research

Working Conditions

  • Travel may be required for training, conferences, etc.
  • Must possess a smart-phone or electronic device capable of downloading applications, for multifactor authentication and security purposes
  • Physical Demands: While performing the duties of this job, the employee is occasionally required to move around the work area; Sit; perform manual tasks; operate tools and other office equipment such as computer, computer peripherals and telephones; extend arms; kneel; talk and hear
  • Mental Demands: The employee must be able to follow directions, collaborate with others, and handle stress
  • Work Environment: The noise level in the work environment is usually minimal

Med-Metrix will not discriminate against any employee or applicant for employment because of race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), political affiliation, military service, veteran status, other non-merit based factors, or any other characteristic protected by federal, state or local law.
Originally posted on Himalayas

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