Bryson Kyle

Led development and deployment of AI-driven features in web applications, integrating LLM-powered services to enhance personalization. Optimized RESTful and GraphQL APIs boosting system throughput by 20%. Transitioned infrastructure to microservices and Docker for scalable AI inference services handling 40% more real-time traffic. Migrated pipelines to AWS reducing costs by 15% and increasing resilience. Implemented automated testing achieving 85% coverage and lowered production errors by 25%. Mentored junior engineers and established security-first culture ensuring data compliance.

At SciSpace in Bangalore, I designed and deployed end-to-end AI-driven features integrated with React/Node.js web applications to enhance personalization and user experience. I developed and optimized RESTful and GraphQL APIs, improving model-serving latency and system throughput by 20%. I led the migration to microservices and Docker architecture, supporting a 40% increase in real-time traffic. I migrated AI pipelines to AWS, reducing operational costs by 15% and increasing system resilience. I implemented automated testing frameworks achieving 85% coverage and lowering production errors by 25%. I partnered with product teams to accelerate AI-assisted feature releases and optimized MongoDB queries, cutting data retrieval time by 25%. I introduced serverless AI execution via AWS Lambda, reducing infrastructure overhead by 22%. Additionally, I mentored junior engineers and established a security-first AI engineering culture ensuring data compliance and safeguards for sensitive datasets.

Designed and deployed AI-driven features in web applications, integrating large language model-powered services into React/Node.js systems to enhance personalization and user experience. Developed and optimized RESTful and GraphQL APIs, improving model-serving latency and boosting throughput by 20%. Led transition to microservices and Docker architecture enabling independent scaling, supporting 40% increase in real-time traffic. Migrated AI pipelines and infrastructure to AWS services, reducing costs by 15% while increasing system resilience. Implemented automated testing frameworks with 85% coverage and lowered production errors by 25%. Partnered with product and design teams to accelerate AI-assisted content discovery features by 20%. Optimized MongoDB queries reducing data retrieval time by 25%. Introduced serverless AI model execution via AWS Lambda reducing infrastructure overhead by 22%. Mentored junior engineers, increasing onboarding speed and team productivity by 20%. Establis