Senior AI Engineer

Designed and delivered production AI features integrating LLM APIs, retrieval workflows, and structured generation capabilities into healthcare applications serving 1M+ patient records. Built backend services using Python and TypeScript to orchestrate AI workflows, manage context, validate outputs, and connect LLM capabilities with existing business systems. Developed RAG-based knowledge workflows using embeddings and semantic retrieval. Implemented AI quality monitoring, validation workflows, and feedback loops reducing inconsistent AI responses by 30%. Collaborated with product and engineering teams to ship AI features from prototype through production release.

Built and maintained production AI applications using Node.js, TypeScript, Python, and LLM APIs supporting 20+ automated business workflows. Designed agentic workflows using tool integrations, structured outputs, context injection, and multi-step reasoning patterns for intelligent task execution. Developed RAG pipelines combining document ingestion, embeddings, vector retrieval, and LLM generation across 100K+ knowledge records. Created prompt optimization and evaluation processes to improve response consistency, reducing hallucination-related failures by 35%. Integrated AI services with internal APIs, databases, and automation platforms.

Developed scalable backend services and user-facing applications using JavaScript, Node.js, SQL, and REST APIs. Built integrations between healthcare platforms and external systems through 30+ production API connections. Optimized database queries and backend workflows improving application performance by 25%. Implemented testing, deployment, and monitoring practices supporting reliable production releases. Collaborated with cross-functional teams to translate business requirements into maintainable software solutions.