AI Engineer with health Care Experience : Remote

Role: AI Engineer Domain: Healthcare / Medicaid Technology Focus: AWS Bedrock, Agentic AI, Python, Databricks Location: US Remote Role Summary We are looking for a hands-on AI Engineer to build enterprise Generative AI and Agentic AI capabilities for a healthcare analytics platform. The engineer will work closely with the AI Architect to implement conversational AI, agent workflows, governed enterprise-data access, and production-ready integrations using AWS Bedrock. Key Responsibilities Build Generative AI and Agentic AI capabilities using AWS Bedrock. Develop AI agents, multi-step workflows, tool/function calling, and orchestration components. Implement prompt engineering, context management, RAG/grounding, and response-validation patterns. Integrate AI services with enterprise APIs, structured data sources, Databricks, and Unity Catalog. Support natural-language interaction with enterprise data, including conversational analytics and NL-to-SQL use cases. Implement secure data-access patterns, guardrails, retry/fallback handling, logging, and observability. Work with the AI Architect, ReactJS developers, QA, and client technical teams to deliver end-to-end AI use cases. Support healthcare security and privacy requirements, including PHI/PII protection and role-based access. Participate in technical design, code reviews, troubleshooting, testing, and production-readiness activities. Must-Have Skills Strong hands-on experience with AWS Bedrock. Hands-on experience building Generative AI / LLM applications. Experience with Agentic AI, AI agents, and tool/function calling. Strong Python development skills. Prompt engineering, context engineering, RAG, and grounding techniques. REST API and enterprise integration experience. Experience working with structured enterprise data and SQL. Understanding of AI security, scalability, monitoring, and production deployment. Strong debugging, problem-solving, and technical communication skills. Preferred Skills Databricks and Unity Catalog experience. Experience leveraging Unity Catalog as a context / metadata plane for AI systems. Experience using Databricks Medallion Architecture as the governed data source for AI applications. LangGraph or a similar agent orchestration framework. Amazon Bedrock AgentCore and Bedrock Guardrails. MCP (Model Context Protocol) and enterprise tool integration. Natural Language-to-SQL / conversational analytics. Vector databases, semantic search, AI observability, and model evaluation. Healthcare / Medicaid / Pharmacy or other regulated-domain experience.