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Puruhuthika y
Mid-level Software Engineer specializing in backend engineering and applied AI workflows
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About
Backend engineer with fintech/transaction-processing experience who built and optimized a Spring Boot + PostgreSQL + AWS service handling money transactions, resolving peak-traffic latency via query/index and connection pool tuning. Shipped an LLM-driven risk-flagging workflow integrated via a FastAPI Python service, owning prompt design, validation guardrails, monitoring, and human-in-the-loop escalation to reduce false positives and improve precision over time.
Experience
Education
Key Strengths
- Backend API development for financial transaction processing systems
- Performance tuning under peak traffic (query optimization, indexing, connection pool tuning)
- Strong SQL debugging approach (profiling, execution plans, reducing joins, selecting required columns, pagination)
- End-to-end LLM feature delivery (FastAPI service, prompt design, validation, integration with Spring Boot, monitoring and iteration)
- Production AI guardrails (validation, thresholds, monitoring, audit logs, human-in-the-loop fallbacks)
- Reliable multi-step workflow/agent design (planning vs execution, retries with backoff, escalation with full context/logs)
- Concurrency correctness in Python services (transactions, row-level locking, idempotent operations)
- Maintainable Python engineering practices (layered architecture, typing/Pydantic, Docker, pytest, dependency pinning)
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