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Rupesh Maddukuri
Mid-level Full-Stack Java Developer specializing in FinTech microservices
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About
Backend-focused Python/Flask engineer with strong performance and scalability experience across PostgreSQL/SQLAlchemy optimization, caching, and async processing. Has implemented multi-tenant data isolation (schema/db per tenant with RBAC and encryption) and integrated TensorFlow-based ML inference behind a Flask REST API using Redis caching, batching, and async execution; reports measurable wins like cutting endpoints from 6–8s to ~2s and increasing throughput 3–4x via Celery queues.
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Key Strengths
- Designed maintainable Flask backend with clear route/service/DB separation
- Improved high-concurrency performance via indexing, query optimization, and caching
- Implemented cache invalidation (TTL) and selective cache busting to reduce stale data
- Reduced slow report endpoint latency from 6–8s to ~2s using profiling and ORM/query tuning
- Integrated ML model serving via REST API with in-memory model loading and Redis caching
- Stabilized ML inference under peak load using batching and async processing
- Built multi-tenant data isolation using schema/database per tenant with middleware routing and RBAC
- Scaled background processing by moving synchronous work to Celery+Redis; achieved ms-level API responses and 3–4x throughput
- Implemented reliable async job handling with retries, dead-letter queues, and Prometheus-based monitoring/alerts
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