AIML Architect

AI/ML Architect

Hybrid Role (2 to 3 days onsite)

Location: Raritan NJ

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 GCP 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 (GCP 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