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Prathamesh Pramod Dhawale
Mid-Level Software Engineer specializing in backend, data platforms, and FinTech systems
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About
Backend engineer with experience at HSBC and Machinations who has delivered major production performance wins (cutting large trade-file upload times from ~13–15s to ~2s) using chunked parallel processing with strong reliability controls. Also built and shipped an applied AI RAG workflow using Langflow + Cohere embeddings + FAISS with hosted/local LLM fallbacks (Hugging Face, Ollama) and production-grade guardrails, observability, and evaluation.
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Key Strengths
- Reduced large Excel trade-file upload latency from ~13–15s to ~2s via chunked parallel processing
- Designed reliability safeguards for parallel ingestion (idempotency, transactions, retries, per-chunk error handling)
- Performance tuning with measurement discipline (before/after timings, EXPLAIN, DB stats, p95 monitoring, load testing)
- Built and shipped end-to-end RAG system (crawl/ingest → embed/index → retrieve → grounded answer) with hosted + local LLM paths
- Implemented AI production guardrails and ops (retrieval confidence thresholds, observability, eval test sets, fallbacks, audit logs)
- GraphQL backend optimization (addressed N+1/joins via batching and indexing)
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