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Ramcharan Reddy
Mid-level Full-Stack Developer specializing in FinTech platforms and cloud-native microservices
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About
Backend engineer focused on AI-enabled systems, having built a production-style RAG pipeline (vector search + LLM) exposed via Python/Flask endpoints with strong observability and hallucination-reduction techniques. Demonstrates deep performance work in PostgreSQL/SQLAlchemy (5x faster analytics queries) and high-throughput optimization using Celery + Redis (800ms to 120ms latency, 3x throughput), plus schema-per-tenant multi-tenancy with tenant-aware middleware and logging.
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Key Strengths
- Built and exposed a RAG pipeline via lightweight REST endpoints (Python/Flask)
- Improved RAG answer accuracy/consistency while controlling cost via retrieval tuning and response verification
- Implemented observability for latency and embedding quality
- PostgreSQL/SQLAlchemy performance tuning (indexes, eager loading, batching, pooling)
- Reduced analytics query times by >5x using EXPLAIN-driven optimization and bulk operations
- Designed strict multi-tenant isolation with schema-per-tenant and tenant-aware query scoping
- Reduced API latency from 800ms to 120ms and increased throughput 3x using Celery + Redis caching with lock keys
- Improved system reliability via timeouts, validation, monitoring, API versioning, and containerized tested deployments
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