AI​/ML Architect Azure

AI/ML Architect with Azure Raritan, NJ, Remote Role Summary

Design the architecture for deploying scalable, observable, and compliant AI/ML solutions integrated with clinical workflows and hospital data platforms.

• Architect end-to-end ML pipelines using Airflow, and MLFlow or Vertex AI
• Build containerized model inference systems deployed on Kubernetes with App Dynamics and observability
• Full ownership of model lifecycle: development, deployment, drift monitoring
• Proficient with Google Cloud Platform Vertex AI, Azure ML, container orchestration (K8s, Docker)
• Design architecture to support GenAI workloads (LLMs, embeddings) using Vertex AI or Azure OpenAI
• Define governance and guardrails for deploying agentic systems in clinical workflows
• Implement MLOps patterns: model versioning, rollback, shadow testing
• Define architecture for RAG (retrieval augmented generation) systems using vector databases (e.g., FAISS, Pinecone)
• Deploy LLM-based agents and secure GenAI pipelines (prompt injection protection, moderation, output fallback)
• Support agentic AI orchestration with frameworks like Lang Chain, CrewAI

• 8+ years in data/ML or AI architecture roles
• Deep knowledge of Kubernetes, Docker, Snowflake, cloud-native tools (Google Cloud Platform, Azure)
• Experience with HIPAA-regulated, real-time model deployment

• Experience integrating with Epic, HL7, FHIR, and SMART-on-FHIR
• Working knowledge of LLMs, GenAI tools, Lang Chain, Weaviate, or ChromaDB
• Design real-time inference services integrated with Epic via FHIR APIs
• Ensure HIPAA-compliant encryption, access controls, and audit trails