AI Architect – Agentic AI & Healthcare Platform

We are looking for an experienced AI Architect / Senior LLM Engineer to design and build an enterprise-grade AI platform for the healthcare industry. You will lead the architecture and implementation of intelligent AI solutions that improve clinical operations, automate administrative workflows, and enable healthcare professionals to access trusted medical knowledge through advanced AI technologies. The ideal candidate has hands-on experience building production-ready Agentic AI systems, Multi-Agent architectures, RAG pipelines, and LLMOps using modern AI frameworks and cloud platforms. Responsibilities Design and develop scalable Agentic AI solutions for healthcare applications. Build Multi-Agent Systems using LangGraph, CrewAI, or AutoGen. Develop enterprise Retrieval-Augmented Generation (RAG) pipelines for medical knowledge retrieval. Create AI agents for clinical knowledge assistance, document intelligence, workflow automation, and care coordination. Build and integrate MCP servers and custom AI tools with internal healthcare systems. Optimize prompt engineering, retrieval strategies, and response quality for high accuracy. Implement AI guardrails, evaluation pipelines, monitoring, and observability for production deployments. Deploy secure, scalable AI infrastructure on AWS using Infrastructure as Code and CI/CD best practices. Collaborate with engineering, product, and healthcare stakeholders to deliver reliable AI solutions. Required Skills 5+ years of experience in AI/ML or Generative AI development. Strong expertise in Python and backend API development. Experience with LangGraph, CrewAI, AutoGen, or similar multi-agent frameworks. Hands-on experience with AWS Bedrock, Azure OpenAI, or Vertex AI. Strong understanding of RAG architectures, vector databases, embeddings, and semantic search. Experience with Pinecone, Weaviate, pgvector, or similar vector databases. Knowledge of LLMOps, evaluation frameworks, prompt engineering, and AI observability tools. Experience with Docker, Terraform, CI/CD, and cloud-native deployments. Familiarity with healthcare compliance, security, and responsible AI practices is highly preferred. Preferred Technologies LangGraph CrewAI AutoGen AWS Bedrock Claude GPT-4o Gemini Pinecone pgvector LangSmith Arize Phoenix FastAPI Docker Terraform GitHub Actions MLflow Nice to Have Experience developing AI-powered healthcare platforms. Knowledge of healthcare workflows, clinical documentation, or medical knowledge systems. Experience integrating AI solutions with enterprise applications through APIs and MCP. Familiarity with AI governance, model evaluation, and production monitoring. If you are passionate about building enterprise-scale AI solutions that transform healthcare through Agentic AI and Generative AI, we'd love to hear from you.