Senior Cloud Security Engineer

This is a fully remote position, open to applicants in New Jersey.

📋 Description

• Design and implement a secure cloud architecture across AWS and Azure, encompassing identity, network security, encryption, and key management.

• Implement cloud-native logging, monitoring, and threat detection to enhance visibility and incident response capabilities.

• Develop Infrastructure-as-Code, Policy-as-Code, and automated compliance controls.

• Execute and improve CSPM, CWPP, and CNAPP functionalities.

• Perform threat modeling, security architecture evaluations, and risk assessments for cloud services and applications.

• Design and secure AI/ML environments, covering MLOps pipelines, model security, inference endpoints, and AI governance.

• Assess and mitigate threats specific to AI, such as prompt injection, model poisoning, adversarial attacks, and data leakage.

• Collaborate with engineering and data science teams to implement security-by-design and privacy-preserving controls for regulated data.

• Create automated detections, SOAR playbooks, and AI-driven threat hunting capabilities.

• Lead the technical response to cloud and AI security incidents, including forensic analysis and remediation efforts.

• Design and implement security controls that align with HIPAA, HITRUST, PCI DSS, SOC 2, NIST CSF, and NIST AI RMF requirements.

• Assist in technical readiness, evidence collection, and remediation tasks for security audits and compliance evaluations.

• 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.

• Establish security metrics, communicate technical risks to stakeholders, and recommend ongoing security enhancements.

• Mentor junior engineers and advocate for security best practices across engineering teams.

• Handle patients’ protected health information in strict accordance with HIPAA standards.

• Comprehend and adhere to Information Security and HIPAA policies and procedures.

• Limit access to PHI to the minimum necessary to perform assigned responsibilities.

⛳️ Requirements

• High school diploma or equivalent is required.

• Minimum of 6 years of experience in information security, with at least 4 years focused specifically on cloud security engineering.

• Extensive hands-on experience with AWS and Microsoft Azure, including AWS GuardDuty, Security Hub, IAM Identity Center, Microsoft Defender for Cloud, Sentinel, and Entra ID.

• Strong knowledge of IAM, zero trust architecture, network security, encryption, and secrets management within cloud environments.

• Practical experience in securing AI/ML systems or LLM-based applications, or demonstrable working knowledge of OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF.

• Proficient in at least one scripting or programming language, preferably Python, and infrastructure-as-code tools.

• Experience with container security and orchestration, including Docker, Kubernetes, EKS, and AKS.

• Solid understanding of DevSecOps practices and integration of CI/CD security.

• Hands-on experience supporting compliance programs for 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 with the ability to communicate effectively at all organizational levels.

• Excellent problem-solving and creative skills, with sound judgment and the ability to make decisions based on accurate and timely analyses.

• High integrity and reliability, complemented by a strong sense of urgency and results orientation.

• Exceptional written and verbal communication skills are required.

• Travel may be necessary for training and conferences.

• Must possess a smartphone or electronic device capable of downloading applications for multifactor authentication and security purposes.

• Experience with GCP in addition to AWS and Azure.

• Experience in deploying or securing MLOps platforms such as SageMaker, Vertex AI, Azure ML, Databricks, or Kubeflow.

• Familiarity with AI-driven security platforms and custom detections using ML techniques.

• Relevant certifications such as CISSP, CCSP, HCISPP, CCSFP, AWS Security Specialty, AZ-500, GCP Professional Cloud Security Engineer, or GIAC certifications.

• Prior experience in healthcare, health tech, or revenue cycle management environments involving PHI at scale.

• Experience with red teaming or adversarial testing of AI systems.

• Knowledge of data privacy regulations regarding AI training data and model outputs, including HIPAA de-identification standards.

• Contributions to security communities, open-source tools, or published research.

• Ability to meet the stated physical and mental job demands.

🏝️ Benefits

• Travel may be required for training, conferences, and other related events.

• Multifactor authentication and security measures supported through a smartphone or electronic device capable of downloading necessary applications.