Luke Davis

Led a distributed engineering team delivering a cloud-native patient engagement and analytics platform built with Java, Spring Boot, Kubernetes, PostgreSQL, Apache Kafka, and AWS, solving complex scalability challenges across hundreds of clinic locations while supporting large-scale operational reporting and low-latency business intelligence workloads. Architected high-performance data processing services and analytical pipelines utilizing distributed computing patterns, event-driven microservices, Elasticsearch, Redis caching, and cloud object storage, enabling executive teams to access near real-time operational insights from millions of customer records and appointment events. Designed AI-powered customer interaction workflows using OpenAI APIs, vector search technologies, recommendation engines, and automated service classification systems that reduced manual support workload by approximately 2,400 requests monthly. Implemented advanced observability solutions using Prometheus, Gra

Worked within a multidisciplinary engineering and data science team building a healthcare analytics platform that processed large clinical datasets using Java, Python, Apache Spark, Kubernetes, PostgreSQL, and AWS infrastructure to improve research accessibility and operational decision making. Designed AI-assisted patient risk analysis workflows that addressed data quality inconsistencies, feature extraction bottlenecks, model deployment challenges, and explainability requirements while integrating machine learning pipelines into enterprise-grade production systems. Developed distributed backend services and scalable ETL pipelines capable of processing more than 14 million healthcare records while maintaining regulatory compliance, auditability, and secure data governance practices. Implemented cloud-native monitoring, automated testing, and infrastructure-as-code deployments that stabilized platform releases and supported continuous delivery across multiple environments. Partnered wi

Developed cloud-based investment platform services using Java, Spring Boot, React, PostgreSQL, and AWS, supporting secure asset management workflows and scalable transaction processing. Built microservice integrations for identity verification, KYC/AML compliance providers, payment systems, and reporting engines that streamlined onboarding operations across thousands of investor accounts. Improved API throughput and database performance through query optimization, Redis caching, and asynchronous processing, enabling faster execution of portfolio management functions.