Interview : Video
Visa : USC, GC, GC EAD, H4
This is hybrid from day-1 ( Local candidates highly preferred )
Description:
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