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mahesh narne
Senior Full-Stack Software Engineer specializing in cloud-native microservices and web apps
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Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.
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Key Strengths
- End-to-end ownership of customer-facing backend services (design through rollout)
- Rapid iteration with quality controls (vertical slicing, strong test coverage, automated pipeline checks)
- Production-safe delivery practices (feature flags, canary rollouts, fast rollback/hotfix mindset)
- Performance and reliability engineering (latency focus, Redis caching built into feature work)
- Microservices at scale on Kubernetes with autoscaling and SLO-driven alerting/on-call
- Event-driven consistency patterns (Kafka events, idempotent consumers, service-owned data models)
- Built internal observability tooling adopted across teams, reducing time to detect/debug incidents
- Strong prioritization in ambiguous environments (stakeholder alignment, impact/risk ranking, smallest valuable slice)
- Designed modular Flask services using blueprints for maintainability
- Operational observability: structured JSON logging, CloudWatch dashboards/metrics, and targeted alerting
- Production error monitoring with Sentry and on-call alert workflows
- SQLAlchemy/PostgreSQL performance tuning aligned to query patterns (indexes, pooling, partitioning/archiving)
- Loosely coupled OCR/ML workflow design using AWS Textract + stepwise Lambda functions
- Reduced request-path latency by offloading heavy document processing to background/event-driven tasks
- Improved high-traffic endpoint performance with Redis read-through caching to reduce DB load
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