AI/ML Architect with 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.

Responsibilities

Architect end-to-end ML pipelines using Airflow, and MLFlow or Vertex AI

Build containerized model inference systems deployed on Kubernetes with AppDynamics 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 LangChain, CrewAI

Required Qualifications

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

Preferred Qualifications

Experience integrating with Epic, HL7, FHIR, and SMART-on-FHIR

Working knowledge of LLMs, GenAI tools, LangChain, Weaviate, or ChromaDB

Design real-time inference services integrated with Epic via FHIR APIs

Ensure HIPAA-compliant encryption, access controls, and audit trails

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