Senior Cloud Security Engineer

Med-MetrixParsippany-Troy Hills, NJ

About The Position

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.

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

Nice To Haves

  • 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

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
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service