Senior Cloud Security Engineer

Med-Metrix is seeking a Senior Cloud Security Engineer to lead security across its multi-cloud environment. The role focuses on securing AWS and Azure infrastructure, AI/ML workloads, DevSecOps processes, compliance controls, and incident response while partnering with engineering, application development, and data science teams.

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

Requirements:

• 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
• 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