Lead AI Governance & Cloud Architect

Summary

This role sits at the intersection of AI innovation, cloud infrastructure, governance, and enterprise security. The Lead AI Governance & Cloud Architect will design and lead the secure framework powering enterprise-wide adoption of Claude Enterprise and advanced LLM technologies across a nationwide healthcare environment.

This is both a strategic and hands-on architecture position focused on building secure AI environments, implementing governance frameworks, and creating the operational controls required to scale AI responsibly within HIPAA- and SOC2-regulated systems.

The ideal candidate brings deep expertise in cloud architecture, enterprise AI governance, observability, and secure infrastructure design within highly regulated environments.

Responsibilities

• Architect secure, isolated AI infrastructure environments across Azure and containerized platforms
• Design enterprise governance frameworks for scalable and compliant AI operations
• Establish controls for PHI/PI handling, prompt security, identity management, and AI usage policies
• Partner with security and compliance teams to maintain HIPAA and SOC2 readiness
• Build enterprise observability and telemetry frameworks for LLM operations and AI governance
• Implement monitoring systems to detect hallucinations, prompt injection risks, model drift, unsafe outputs, and data leakage
• Develop logging, auditability, alerting, and AI operational monitoring capabilities
• Establish enterprise guardrails and safe deployment standards for AI systems
• Architect scalable Azure and Docker-based environments optimized for AI workloads
• Design secure networking, VPC isolation, and container orchestration strategies
• Develop deployment standards and CI/CD pipelines for AI and LLM-based systems
• Lead Claude Enterprise implementation and enterprise operationalization efforts
• Build token optimization, prompt caching, and AI cost-governance frameworks
• Define secure promotion workflows across development, staging, and production environments

Requirements

• 7+ years of experience in cloud architecture, infrastructure engineering, or platform engineering
• Proven experience deploying and governing enterprise AI or LLM solutions in production environments
• Deep expertise with Anthropic Claude Enterprise, AWS Bedrock, Azure OpenAI, or similar platforms
• Strong background in Azure infrastructure, Docker, secure networking, and private environment design
• Experience implementing LLMOps and observability tooling such as LangSmith, OpenTelemetry, DataDog for LLMs, or prompt monitoring platforms
• Strong understanding of HIPAA, PHI/PI handling, SOC2 readiness, and enterprise AI governance
• Experience building CI/CD pipelines and deployment standards for AI or machine learning systems
• Excellent communication and leadership skills with the ability to operate across technical and executive stakeholders