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Tier-1 brand, metro location, mid-level AI title, and broad skills amplify candidate competition.
Core LLM and deployment skills transfer across industries, though healthcare interoperability and compliance increase domain sensitivity.
Explicit 6+ years requirement plus mandatory LLM, RAG, Azure, and vector DB skills make screening highly strict.
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Design and develop Large Language Model (LLM) powered healthcare applications including Retrieval-Augmented Generation (RAG) solutions and Agentic AI multi-agent orchestration frameworks.
Implement prompt engineering, evaluation, grounding, safety frameworks, and build AI copilots and decision-support assistants for Prior Authorization Automation.
Collaborate with Product, Engineering, and Data Science teams to deliver production-ready AI capabilities while supporting Responsible AI governance and model observability.
6+ years of software engineering or AI experience.
Strong Python development skills.
Hands-on experience with LLMs, RAG, prompt engineering, agent frameworks (e.g., LangGraph, CrewAI, Semantic Kernel, AutoGen), and vector databases.
Experience with Azure OpenAI or Azure AI Services and deploying AI solutions in production environments.
Experience in healthcare domains such as Prior Authorization, Claims, or Revenue Cycle Management is preferred.
Familiarity with AI evaluation and observability tools and healthcare interoperability standards like FHIR, HL7, or Epic increases competitiveness.
Able to operate at senior technical levels designing and deploying complex AI systems in regulated healthcare environments.