Aadish Aayush

Designed and maintained 6 core microservices managing printer firmware, licensing, embedded apps, and product configurations supporting 100+ product variants and serving 10+ internal teams. Led and mentored a 2-member dev team, improving sprint delivery rates by 25% through focused domain training and code quality practices. Executed a complete tech stack upgrade from Java 8 to Java 17, Spring Boot 2.x to 3.x, and Gradle 5.x to 7.x, resulting in a 35% reduction in build times and enhanced maintainability. Delivered 10+ REST APIs for bridge firmware management and compatibility readme generation used in 90% of deployment workflows. Streamlined CI/CD using Jenkins, Azure DevOps, and Git, reducing deployment errors by 30% through automated validation pipelines. Contributed to a proprietary configuration platform used by 200+ enterprise customers with 7000+ devices deployed globally. Enhanced LRMe, a Java-based remote agent, improving reliability of configuration job deployments worldwide. Migrated communication from blocking RestTemplate to non-blocking WebClient, boosting scalability under high concurrency. Resolved 30+ high-priority issues, cutting incident resolution time by 40%. Applied patches to remediate 20+ critical CVEs, ensuring compliance and reducing vulnerabilities. Supported backend CRUD services and internal tool Config Tool for configuration task assignment. Built a front-end application in Angular to allow business users to create and manage business rules demonstrating proficiency in modern Angular development. Programmatically generated and validated Camunda DMN decision tables from business-defined rules, enabling controlled promotion from test to production in a Java-based microservice. Designed and implemented scalable data pipelines on Databricks using PySpark, Delta Lake, SQL, and Python to support ML-based forecasting of printer consumable usage. Processed and structured 250GB+ telemetry data within a Medallion architecture, enabling consistent and high-quality input for ML models and downstream logic. Developed post-prediction business workflows to simulate automated alarm triggers and order generation, helping reduce consumable stockouts in simulated field conditions. Managed automated workflows in Azure Pipelines to run business rules and alarm evaluations on processed data, supporting internal validation and order simulation use cases.