Senior Cloud Security Engineer

Job description

**This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Cloud Security Engineer based in the United States.** We are seeking an experienced cloud security professional to strengthen the security, resilience, and compliance of modern cloud-based healthcare platforms. In this role, you will lead the design and continuous improvement of secure AWS environments while protecting sensitive patient information and supporting advanced AI-driven technologies. You will establish security architectures, implement Zero Trust principles, and integrate automated controls across cloud infrastructure and software delivery pipelines. Working closely with engineering, data science, compliance, and enterprise technology teams, you will address emerging risks associated with machine learning, generative AI, and autonomous AI systems. You will also drive threat detection, incident response, and regulatory readiness while mentoring colleagues and promoting security best practices. This is an opportunity to make a meaningful impact at the intersection of healthcare innovation, cloud engineering, and next-generation AI security in a remote-friendly environment. ### Accountabilities - Design secure cloud architectures: Lead the design, implementation, and continuous improvement of secure AWS environments, ensuring infrastructure and applications meet organizational security standards. - Establish security guardrails: Develop and enforce cloud security policies and standards covering identity and access management (IAM), network segmentation, encryption, logging, and other critical controls. - Implement Zero Trust principles: Apply Zero Trust architecture across cloud-native systems, user endpoints, identity workflows, and access management processes. - Secure cloud workloads: Protect containerized and serverless environments, including Kubernetes, Docker, Amazon ECS, and AWS Lambda, and assess existing implementations to prioritize remediation of security weaknesses. - Strengthen workforce security: Improve endpoint security, identity lifecycle management, privileged access management (PAM), and secure virtual desktop infrastructure (VDI) supporting access to protected health information (PHI). - Secure AI and machine learning systems: Define security controls for AI/ML and generative AI applications, addressing threats such as prompt injection, model poisoning, data leakage, and adversarial attacks. - Protect autonomous AI workflows: Develop security approaches for agentic AI systems, including autonomous workflows and decision-making agents, and collaborate with data science teams to embed security throughout the model development lifecycle through MLSecOps practices. - Support regulatory compliance and risk management: Partner with governance, risk, and compliance (GRC) teams to maintain alignment with HIPAA, HITRUST, SOC 2, and other applicable requirements. - Conduct security assessments: Perform threat modeling and risk assessments across cloud infrastructure and AI systems, document findings, and support audits and compliance initiatives. - Improve detection and incident response: Implement and optimize security monitoring and detection capabilities using SIEM, cloud security posture management (CSPM), and cloud workload protection platforms (CWPP). Develop automated remediation workflows and support incident response for cloud security events. - Integrate security into development: Apply static application security testing (SAST), dynamic application security testing (DAST), and software composition analysis (SCA), including appropriate use of AI-assisted coding tools. - Automate security controls: Integrate security scanning, policy enforcement, and compliance checks into CI/CD pipelines and infrastructure-as-code workflows using tools such as Terraform and CloudFormation. - Promote DevSecOps practices: Work closely with engineering teams to embed security early in the software development lifecycle and reduce vulnerabilities before deployment. - Mentor and influence teams: Guide engineers and security analysts, share technical expertise, and encourage consistent adoption of security best practices across the organization. - Monitor emerging threats: Stay informed about evolving cloud, cybersecurity, and AI-related risks, translating new developments into practical security improvements. - Collaborate across functions: Partner with product, engineering, people operations, enterprise systems, data science, and external stakeholders to support business objectives and security priorities. ## Requirements: - Education: Bachelor's degree in Cybersecurity, Computer Science, Information Systems, or a related field, or equivalent practical experience. A master's degree in a relevant discipline is desirable. - Professional experience: At least five years of experience in cloud security or cybersecurity engineering, with hands-on responsibility for designing, implementing, and improving security controls. - AWS expertise: Strong practical experience securing AWS services and applying cloud security principles across identity management, networking, encryption, logging, and infrastructure protection. - Cloud-native security: Solid understanding of containerized environments, including Kubernetes and Docker, as well as serverless architectures and cloud-native application security. - Regulated environments: Strong knowledge of security and compliance requirements in regulated industries, particularly HIPAA, HITRUST, and SOC 2. - Zero Trust architecture: Experience implementing Zero Trust principles across cloud infrastructure, endpoints, identity, and access controls. - AI security knowledge: Experience identifying and mitigating security risks associated with AI technologies, including machine learning, generative AI, and emerging autonomous AI systems. - DevSecOps and automation: Demonstrated ability to automate security controls and integrate security testing into CI/CD pipelines and infrastructure-as-code workflows. - Programming and scripting: Proficiency in at least one programming or scripting language, with familiarity with Python, Java, Node.js, or C#. - Application security testing: Hands-on experience with SAST, DAST, and SCA tools, along with an understanding of how AI-assisted coding tools affect software security. - Security monitoring and response: Knowledge of cloud security monitoring, threat detection, vulnerability remediation, and incident response processes. - Security certifications: CISSP, CCSP, AWS security certifications, or comparable credentials are highly desirable. - Technical leadership: Ability to guide and influence engineers, security analysts, and other technical professionals without necessarily having direct managerial authority. - Communication and collaboration: Strong interpersonal and communication skills, with the ability to explain complex security issues and collaborate effectively across technical and business teams. - Problem-solving and adaptability: Strong organizational skills, sound judgment, prioritization, motivation, and the ability to respond effectively to evolving security challenges. - Travel availability: Willingness to travel occasionally to the organization's Tennessee offices for training. - Work authorization: Must already be authorized to work in the United States on a full-time, permanent basis without requiring current or future visa sponsorship. - Pre-employment screening: Successful completion of a background check is required due to access to sensitive information, including proprietary data and protected health information. ## Benefits: - Medical, dental, and vision insurance to support employee health and well-being. - 401(k) retirement plan with employer matching to help employees plan for the future. - Flexible paid time off to support work-life balance. - Paid parental leave for eligible employees. - Health Savings Account (HSA) and Flexible Spending Account (FSA) options to help manage eligible healthcare expenses. - Educational reimbursement program to support continued learning and professional development. - Employer-paid Employee Assistance Program (EAP) and mental health services. - Remote work opportunity within the United States, with occasional travel to Tennessee for training. - Meaningful technical impact: The opportunity to strengthen security for AI-enabled healthcare technology and help protect sensitive patient data. - Professional growth: Exposure to cloud security architecture, emerging AI threats, regulated healthcare environments, and cross-functional technical leadership.