Generative AI Engineer

Rate:~$82/hr.Location: Nashville, TNDuration: ~6 month contract to HIRENOT eligible to work C2CThe Staff Agentic AI Engineer will provide crucial engineering leadership in the application of advanced Generative AI, supporting the revolutionization of healthcare by designing and implementing cutting-edge AI solutions. The Staff Agentic AI Engineer will be instrumental in developing systems that leverage Generative AI, particularly with GCP Vertex AI, Gemini, and related tooling, to create transformative products for users across the company's ecosystem. This role will focus on practical applications of AI, including Retrieval-Augmented Generation (RAG), the design of sophisticated grounding data structures, and the construction of robust pipelines for grounding and embedding.Required Skills & Experience• 5-8 years of experience as a Software Developer or Engineer, moved into Solutions Architecture (Not Data Engineer)• Recent 2-3 years understanding and practical experience in designing and building Agentic AI - Retrieval-Augmented Generation (RAG) architectures (NOT ML/Ops Models)• Design, extend, and operationalize AI creation tools and intelligent agents leveraging advanced models.• Secure, deploy, and productionize AI agents to ensure scalability, reliability, and compliance.• Build or integrate Model Context Protocols (MCP) to support robust agent–model interactions. Develop agentic capabilities tailored to specific use cases, workflows, and functional requirements. • Hands-on experience with Google Cloud Platform Vertex AI, or Azure AI Foundry, or Foundational Models• Experience building cloud-native solutions using serverless and/or container-based architecture• Full-stack working experience with Pyton, Java, C#, Node.js, SQL/NoSQL database, ETL/data pipelines, messaging queues/event streaming, docker/Kubernetes, microservices – Need at least 4 to proceedNice to Have Skills & Experience• Delivered Generative AI applications into production at scale in a customer-facing or enterprise environment • Built or supported data pipelines for embedding and vector stores • Designed and implemented Retrieval – Augmented Generation Systems • Designed grounding strategies or data structure to connect LLMs with enterprise or real time information sources • Familiarity with Agentic AI concepts and frameworks (e.g., LangChain) for building autonomous and multi-agent systems