AI / ML Architect :
Raritan, NJ, 3 days Hybrid Contract 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 rolesDeep 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-FHIRWorking knowledge of LLMs, GenAI tools, LangChain, Weaviate, or ChromaDBDesign real-time inference services integrated with Epic via FHIR APIsEnsure HIPAA-compliant encryption, access controls, and audit trails