Description

You will design and implement applied AI solutions for a healthcare client, focusing on LLMs and NLP.

This role is on-site.

Responsibilities

• Design AI agent architectures using LLMs and NLP techniques.
• Develop solutions utilizing Agent-to-Agent protocols and Model Context Protocols (MCP).
• Build and maintain data pipelines integrating healthcare standards like FHIR, HL7, ICD/CPT, and X12 EDI.
• Deploy models within cloud-native environments using Kubernetes and Docker.

Required Skills

• 7+ years of applied AI experience with LLMs and transformers in healthcare.
• Hands-on experience with LangGraph, AutoGen, and CrewAI.
• Proficiency in Python and core ML/NLP libraries including PyTorch, LangChain, and spaCy.
• Experience implementing Agent-to-Agent protocols.
• Familiarity with healthcare data standards (FHIR, HL7, ICD/CPT, X12 EDI).
• Experience with major cloud providers: AWS, Azure, or GCP.
• Working knowledge of containerization (Docker) and orchestration (Kubernetes).
• Experience with CI/CD practices.

Key Skills

Education

Any Graduate