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Charmil Shah
Mid-level Full-Stack Developer specializing in FinTech and cloud-native web apps
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About
Backend engineer who built a containerized Flask service powering an engineering metrics dashboard by syncing GitHub and Jira data into PostgreSQL, with strong emphasis on schema design, query performance, caching, and background processing. Has hands-on experience with SaaS multi-tenancy (tenant scoping + Postgres RLS) and integrating AI/ML inference via separate model-serving services (FastAPI + TensorFlow Serving) and external APIs (OpenAI/Hugging Face/PyTorch).
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Key Strengths
- Designed and built Flask backend using blueprints + app factory for modularity
- Strong database/schema design for reporting (FKs, indexing) with PostgreSQL/SQLAlchemy
- Performance tuning: avoided N+1 queries; used eager loading and aggregations; leveraged query plans
- Built scheduled background sync to external systems (GitHub/Jira) to keep APIs responsive
- Implemented reliability/security features: JWT auth, centralized error handling, Redis caching
- Multi-tenant data isolation using tenant scoping plus PostgreSQL Row-Level Security
- High-throughput background processing optimization (batching, caching, dynamic worker scaling) reducing queue latency from minutes to seconds
- Integrated AI/ML inference via separate model-serving services (FastAPI + TensorFlow Serving) with batching/timeouts/fallbacks
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