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Akhil Jaggari
Mid-level Full-Stack Software Engineer specializing in scalable web platforms and cloud microservices
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Backend engineer with fintech/real-estate lending domain experience (Berkadia) building Python/Flask services for indicative loan pricing across Fannie/Freddie workflows. Strong in scalable AWS architectures (S3, Lambda, SageMaker), database performance (PostgreSQL read replicas, indexing, pooling), and high-throughput optimizations (streaming exports, Redis caching) with measurable production impact.
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Key Strengths
- Built and maintained Python/Flask backend services for indicative loan pricing (Fannie/Freddie) including property search, loan calculations, and Excel workflows
- Improved API performance ~40% via Redis caching of frequently accessed loan/property data
- Designed scalable file/export architecture using S3 pre-signed URLs and AWS Lambda async processing to avoid blocking API requests
- Optimized PostgreSQL/SQLAlchemy performance with lazy loading, connection pooling, composite indexes, and bulk operations
- Implemented read/write separation with PostgreSQL read replicas and SQLAlchemy routing at the repository layer
- Integrated ML inference into backend via SageMaker endpoints with Celery/RabbitMQ async calls and Redis caching
- Designed multi-tenant data isolation with tenant-ID enforcement, RBAC via Keycloak, and audit logging
- Resolved production export failures (>50k rows) by redesigning to streaming + background processing; ~90% export improvement and >30% memory reduction
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