Back End Software Engineer
Project Overview: AI Technologies - Safety Platform Integration with AI/ML ● Dedicated to Australia Clients as a Backend Server developer, work closely with project stakeholders and relative team to involving in building an Android application that integrates with AI Technologies and Machine Learning, covering the entire process from requirements to go-live. ● The project involved integrating AI tools into workflows to classify user intent, fine-tune documents, generate responses using ChatGPT, and inquire about company policies related to uploaded organizational documents. It also included activating emergency services, team-call, manager-call, and peer-to-peer call functionalities, as well as incorporating internal notifications. Key responsibilities: ● Architected and optimized a scalable, microservices-based backend for an AI-integrated Android app, ensuring high availability and maintainability. ● Played a pivotal role in architectural decision-making, contributing to process improvements and long-term technical strategy for backend systems. ● Applied TDD with 95% test coverage, reducing production issues and ensuring code reliability. ● Optimized database performance with advanced SQL, Redis caching, and improved indexing, cutting query latency by 40%. ● Implemented MQTT to push audio file responses to devices, ensuring real-time, low-latency communication. ● Handled S3 integration for secure PDF policy uploads and storage. Implemented functionality to split large PDF files into smaller parts after upload to facilitate faster AI-based searches. ● Developed fault-tolerant communication features, including emergency, team-call, and peer-to-peer service., ● Engineered and optimized worker processes to efficiently handle background tasks, ensuring enhanced system performance, reliability, and scalability. Implemented best practices to streamline task execution, minimizing downtime and resource consumption.