Andrae Browne

Architected AI-driven chatbots and recommendation engines to enhance retention and response time using Python, LangChain, GPT-4, and ML frameworks. Developed over a dozen microservices with Java Spring Boot, Flask, and Kafka, scaling infrastructure for 50K+ monthly active users with high uptime and performance. Built cross-platform applications with React, Next.js, Angular, and React Native, improving code reuse and reducing development time. Enhanced CI/CD pipelines with Jenkins, Docker, and Kubernetes, accelerating releases and lowering defects. Deployed AWS Quicksight and ElasticSearch dashboards to improve data discovery and decision-making. Mentored six engineers, increasing sprint velocity.

Architected AI-driven chatbots and recommendation engines improving retention rates by 30% and speeding up response times by 40%. Developed and scaled 12+ microservices with Java Spring Boot, Flask, and Kafka to handle 50K+ users with 99.9% uptime and 150% performance gains. Engineered interoperable data models across multiple databases reducing retrieval times by 45%. Built cross-platform apps using React, Next.js, Angular, TypeScript, and React Native reducing development time by 25%. Streamlined CI/CD pipelines resulting in accelerated release cycles and lower defect rates. Deployed analytic dashboards increasing data discovery and decision-making efficiency. Mentored engineers enhancing sprint velocity by 25%.

Created ADA-compliant platforms using React, Next.js, Angular, Django, and Node.js to boost accessibility and performance scores. Migrated and modernized services to Spring Boot microservices with AWS Lambda, Kafka, and Azure Functions, later ported to GCP, reducing costs and improving uptime. Designed and optimized databases resulting in reduced query latency and improved scalability. Integrated LLM-powered automation for job matching with LangChain, OpenAI, and ML frameworks, cutting administrative hours and accelerating placement. Optimized CI/CD pipelines and implemented ElasticSearch for improved query precision and reduced latency.