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Xsolis

AI-driven SaaS for utilization management

Senior Cloud Security Engineer

Security Engineering & ArchitectureConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listed

About the Job

Requirements

  • A bachelor's degree in Cybersecurity, Computer Science, or Information Systems, or equivalent working experience.
  • At least 5 years of experience in cloud security or cybersecurity engineering.
  • Strong knowledge of cloud security principles, including identity and access management, networking, encryption, and logging.
  • Hands-on experience using and securing Amazon Web Services services.
  • Experience securing containerized environments, including Kubernetes and Docker.
  • Deep understanding of security in regulated environments, including HIPAA, HITRUST, and SOC 2.
  • Broad experience implementing automation to improve efficiency.
  • Experience implementing Zero Trust Architecture.
  • Proficiency in programming or scripting.
  • Experience identifying AI security risks and securing AI technologies.
  • Ability to work with and indirectly lead a wide range of professionals and team members.
  • Motivation, communication, organization, prioritization, problem-solving, and adaptability.
  • Must pass a background check and be authorized to work in the United States on a full-time, permanent basis without current or future sponsorship.

Responsibilities

  • Design and implement secure cloud architectures across AWS.
  • Lead development of security guardrails, policies, and standards, including identity and access management, network segmentation, and encryption.
  • Implement Zero Trust architecture principles across cloud-native systems and user endpoints.
  • Secure containerized and serverless workloads, including Amazon ECS, Kubernetes, Docker, and AWS Lambda.
  • Assess existing cloud implementations, identify security issues, and prioritize them for remediation.
  • Define and enforce security controls for endpoints and resource access.
  • Improve identity lifecycle management and privileged access management.
  • Partner with engineering teams to design and implement a secure virtual desktop infrastructure environment to support access to protected health information.
  • Define and enforce security controls for AI, machine learning, and generative AI applications.
  • Partner with Data Science to mitigate model poisoning, prompt injection, data leakage, and adversarial attack risks.
  • Secure agentic AI systems, including autonomous workflows and decision-making agents.
  • Collaborate with Data Science teams to embed security into the model development lifecycle (MLSecOps).
  • Collaborate with Governance, Risk, and Compliance teams to support adherence to healthcare regulations, including HIPAA, HITRUST, and SOC 2.
  • Conduct risk assessments and threat modeling for cloud and AI systems.
  • Support audits and compliance initiatives with appropriate controls and documentation.
  • Implement and tune cloud-native security monitoring and detection, including SIEM, CSPM, and CWPP.
  • Develop automated response and remediation workflows.
  • Help manage incident response efforts for cloud security events.
  • Integrate and optimize security in continuous integration and continuous delivery pipelines and infrastructure as code, including Terraform and CloudFormation.
  • Automate security controls, scanning, and policy enforcement.
  • Partner with engineering teams to shift security left.
  • Mentor engineers and security analysts and promote security best practices across teams.
  • Partner with product, engineering, people operations, enterprise systems, and Data Science teams.
  • Stay current on emerging threats in cloud and AI security.
  • Collaborate with internal and external teams to meet business objectives and support company values.
  • Travel to the Tennessee home offices for training.

Desired Qualifications

  • A master's degree in Cybersecurity, Computer Science, or Information Systems.
  • Certifications such as CISSP, CCSP, or AWS Security certifications.
  • Deep experience with static application security testing, dynamic application security testing, software composition analysis, and AI coding tools.
  • Familiarity with Python, Java, Node.js, and C#.

About the Company

Xsolis

AI-driven SaaS for utilization management

Xsolis provides a SaaS platform for healthcare organizations to manage utilization and medical necessity. Dragonfly analyzes real-time EHR data to generate a Care Level Score used by both providers and payers. It combines predictive and generative AI to support clinical workflows, discharge planning, and appeal letters, plus Physician Advisor and Denials Management services. The goal is to reduce administrative waste and speed up decisions by creating a shared view that improves payer-provider collaboration.

Company size
201-500
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$75M
Headquarters
Franklin, TN
Founded
2013

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