Christian Lee Richardson

Led development of an AI conversational agent platform for care service coordination, doctor workflows, and doctor-patient meetings in a healthcare environment requiring secure data handling and reliable payment-related operations.

Designed and built a Healthcare AI Conversational Assistant platform using microservice and micro-frontend architecture with Python, TypeScript, React, and Next.js. Achieved a 15% reduction in system downtime and a 20% improvement in server response times for sensitive patient data processing. Led frontend modernization optimizing page loads via Next.js App Router, SSG/SSR, and code-splitting, cutting development cycles by 50%. Built reusable UI libraries via internal NPM packages to enforce consistent design patterns and accelerate velocity. Integrated GenAI features with OpenAI APIs for automated mental health assessments and personalized clinician insights. Implemented real-time data sync and authentication with Supabase, reducing API latency by 40%. Collaborated with backend teams to maintain microservice-based architectures using RabbitMQ, Kafka, and REST, processing over 2M inter-service messages daily. Containerized with Docker and deployed on Kubernetes on AWS, achieving 99.9%

Improved development lifecycle by 30% across 5 major projects; designed scalable, high-availability microservices; developed RESTful API and GraphQL interfaces with Django and FastAPI; created bulk upload for voice recordings using S3/Lambda; optimized ORM/SQL for analytics pipelines; implemented real-time streaming with WebSockets and Redis caching; used SQS/SNS and Google Pub/Sub for messaging; containerized with Docker and deployed on AWS EKS/ECS; integrated PyTorch/TensorFlow/HuggingFace models for voice and text analytics; built ETL pipelines; fine-tuned transformer models for sentiment and emotion analysis; integrated OpenAI GenAI features and Cursor IDE workflows; connected Twilio/Zoom for notifications and real-time video; achieved ~95% unit test coverage.