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Dev PARIKH
Mid-level Software Engineer specializing in backend systems and applied AI
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Backend/full-stack engineer at Qualcomm who built and operated a drift monitoring platform for 10k+ edge AI models. Stands out for combining strong TypeScript/React/Node execution with production-grade systems thinking across PostgreSQL tuning, Redis caching, ECS deployments, and Kafka-based architectural improvements that measurably improved reliability and release speed.
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Key Strengths
- built full-stack telemetry dashboard for 10k+ edge AI models
- strong end-to-end TypeScript architecture with shared frontend/backend contracts
- designed BFF layer aggregating Prometheus and PostgreSQL into clean APIs
- production-scale caching strategy using Redis and stale-while-revalidate
- PostgreSQL performance tuning with composite and BRIN indexes
- solved storage bloat by moving raw payloads from PostgreSQL to S3
- improved write throughput by batching concurrent ECS worker inserts
- owned production systems post-launch with CI/CD to ECS via GitHub Actions
- reduced false alert rates by 60% through statistically based alerting redesign
- drove Kafka-based architectural decoupling that increased deployment frequency by ~30%
- reduced API timeouts and prevented cascading service failures through async processing
- Built production React/TypeScript telemetry dashboard for 15+ services
- Strong frontend architecture with feature-based component organization
- Sophisticated client/server state separation using Redux Toolkit and React Query
- Performance optimization for high-frequency dashboards using memoization and virtualization
- Type-safe API modeling and refactor-safe TypeScript patterns
- End-to-end ownership across frontend, backend, and data layer
- Designed decoupled ML monitoring system for 20+ edge-deployed models
- Scalable backend architecture using SQS, FastAPI, PostgreSQL, and S3
- Production deployment automation with GitHub Actions, Docker, ECR, and ECS
- Improved alert quality by reducing false positives 60%
- 0-to-1 product execution as a solo builder
- Shipped RAG-based document Q&A platform with sub-300ms retrieval
- Delivered production-ready system supporting up to 100 concurrent users
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