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Mahesh Kota
Mid-level Full-Stack Java Developer specializing in cloud-native FinTech and Healthcare platforms
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About
Backend engineer with production experience building and scaling a Java/Spring Boot payment processing API on AWS (PostgreSQL/Redis) handling a few thousand RPS, including deep performance debugging (connection exhaustion) and observability (CloudWatch, Actuator, Zipkin). Also shipped application-layer AI features (OpenAI email summarizer with feedback loop, ~40% faster agent response times) and designed reliable multi-step workflow orchestration with retries and manual escalation, plus strong SQL tuning and Python engineering practices.
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Key Strengths
- Debugged high-traffic latency by identifying DB connection leaks and implementing HikariCP connection pooling
- Scaled a payment processing API to a few thousand requests per second on AWS with caching and observability
- Built monitoring/alerting using CloudWatch + Spring Actuator metrics and tracked cache hit ratios/DB performance
- Implemented distributed tracing (Zipkin) to detect and diagnose slow requests
- Shipped an OpenAI-powered email summarization feature end-to-end (integration, prompt tuning, feedback loop) reducing support response time ~40%
- Designed fault-tolerant multi-step workflow orchestration with queue-based workers, persisted state machine, retries, and manual escalation
- Improved PostgreSQL query performance from ~8s to <300ms using EXPLAIN ANALYZE, composite indexes, and denormalized summary tables
- Established Python maintainability practices: typing (mypy), lint/format (flake8/black), async (asyncio/aiohttp), background jobs (Celery), and testing (pytest in CI)
- Designed AI production guardrails: observability, evaluation pipelines, drift monitoring, rollback, fallbacks, and human-in-the-loop review
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