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Sahana Mudduluru
Mid-level Full-Stack Engineer specializing in cloud-native FinTech analytics
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Full-stack/ML-leaning engineer who has shipped production-grade real-time analytics and an internal AI support assistant using RAG over enterprise documentation. Demonstrates strong systems thinking across scalability, reliability, observability, and LLM safety/evaluation (thresholded retrieval, RBAC, response validation, regression-gated evals), with concrete iteration based on performance metrics and user feedback.
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Key Strengths
- Owned end-to-end delivery of near real-time analytics ingestion/reporting (idea to launch to iteration)
- Architected scalable event-driven pipelines balancing latency vs cost/complexity (Kafka-based)
- Performance tuning at scale (SQL optimization and indexing to address query slowdowns with growing data volume)
- Built production RAG support assistant grounded in internal documentation with vector search and embeddings
- Strong LLM safety/quality engineering (relevance thresholds, constrained prompting, RBAC filtering, response validation, safe fallbacks, clarification flows)
- Designed evaluation loop with real user queries, SME review, quality metrics, and regression gating; improved retrieval by fixing chunking strategy
- Implemented reliability and observability in data pipelines (retries, DLQs, logging/monitoring/alerting)
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