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Kiran M
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and data platforms
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About
Backend/ML integration engineer with experience at Accenture and Walmart building Flask-based analytics and prediction APIs on PostgreSQL/MySQL. Strong focus on performance and scalability—uses precomputed aggregates, Redis caching, query tuning (indexes/partitioning/EXPLAIN), and async/background processing; also designs secure multi-tenant isolation with JWT and schema/db-per-tenant strategies.
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Key Strengths
- Designed and built analytics/reporting APIs with Flask using layered architecture
- Performance optimization of heavy aggregation workloads via precomputed summary tables and caching (seconds to milliseconds)
- Database performance/scalability tuning with SQLAlchemy + PostgreSQL (indexes, partitioning, query profiling with EXPLAIN ANALYZE)
- Productionizing ML models as API services (model packaging/serialization, consistent feature engineering between training and inference)
- Scalability patterns for ML APIs: load model at startup, stateless services, horizontal scaling (containers/AWS Lambda), queue + batch processing for spikes
- Multi-tenant data isolation using tenant_id filtering plus stronger isolation via schema/db-per-tenant and JWT-based enforcement
- Improved high-traffic e-commerce performance by moving synchronous work to background workers and adding Redis caching to reduce DB load and prevent peak-time timeouts
- End-to-end full stack delivery (backend, frontend, cloud deployment, CI/CD)
- Designed and built Java Spring Boot microservices for inventory, orders, and financial transactions
- Improved transaction throughput by ~22% through performance optimization
- Built responsive React.js UI for an e-commerce platform
- Implemented robust REST API practices (error handling, validation, logging)
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