Senior Enterprise Security Architect, AI Health Cloud

BrightSpring Health Services•Louisville, KY

12d

About The Position

We are seeking a highly experienced Senior Enterprise Security Architect to lead the design, strategy, and governance of enterprise-wide security for our AI Health Cloud platform. This role is responsible for securing cloud-native applications, AI/ML systems, healthcare data ecosystems, and enterprise integrations. You will define the security architecture across platforms, data, APIs, and AI systems, ensuring that all capabilities are secure, compliant, resilient, and aligned with healthcare regulations and Responsible AI standards.

Requirements

12+ years of experience in enterprise security architecture
Strong background in cloud security, identity management, and application security
Experience securing AI/ML platforms and data systems
Deep knowledge of healthcare compliance and data standards
Experience with DevSecOps and modern security tooling
Strong leadership and stakeholder influence

Nice To Haves

Experience with Azure security stack and cloud-native services
Knowledge of LLM security and Responsible AI principles
Familiarity with HITRUST, NIST, ISO 27001 frameworks
Certifications such as CISSP, CCSP, or equivalent

Responsibilities

Define and lead enterprise security architecture across cloud platforms, AI/ML systems, and applications
Establish security standards, policies, and reference architectures
Architect zero-trust security frameworks, identity and access management, and data protection strategies
Secure AI/ML systems including LLMs, RAG pipelines, and model lifecycle
Design API security, encryption, secrets management, and key management
Ensure compliance with HIPAA, CMS, HITRUST, and other healthcare regulations
Partner with engineering, product, and compliance teams to embed security into SDLC and MLOps
Lead threat modeling, risk assessments, and security architecture reviews
Define security design patterns for cloud-native architectures (Azure preferred)
Implement network security, container security (Docker/Kubernetes), and workload protections
Secure AI pipelines including training, inference, and model monitoring
Establish safeguards for prompt injection, data leakage, and model abuse
Integrate security into CI/CD pipelines (DevSecOps)
Define automated security testing (SAST, DAST, SCA)
Implement observability and incident response frameworks
Define security logging, monitoring, and threat detection strategies
Lead risk-based security frameworks and controls
Ensure audit readiness and regulatory compliance
Support governance of data privacy and protection
Define policies for secure data usage across payer, provider, and pharmacy domains