Senior Cloud Security Engineer

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.

• 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 Cloud Formation.
• Promote Dev Sec Ops  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…