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Abhinay Mangasamudram
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
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About
Backend engineer with cloud-native Python/Flask experience building high-throughput financial platforms (loan origination intelligent document processing and real-time fraud detection). Has scaled microservices on AKS with event-driven Azure messaging, delivered measurable performance gains (e.g., 700ms→180ms query latency; ~40% API improvements), and implemented strong security controls (OAuth2/JWT, Azure AD RBAC, audit logging, AES-256/TLS) for sensitive regulated data.
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Key Strengths
- Built Flask microservice integrating Azure Cognitive Services for intelligent document processing in loan origination
- Scaled containerized microservices on AKS to handle ~250K monthly loan applications
- Implemented event-driven async processing with Azure Event Hub/Service Bus, improving synchronous API performance ~40%
- Optimized PostgreSQL queries/pipelines (fraud detection) reducing latency from ~700ms to ~180ms and improving efficiency ~65%
- Improved query execution time ~40% via schema/query optimization across microservices (Hexapay)
- Designed secure APIs with OAuth2/JWT + Azure AD RBAC, audit logging, and encryption (AES-256 at rest, TLS in transit)
- Implemented Celery background task queue to offload heavy jobs and improve API responsiveness under high transaction load
- Experience with multi-tenant isolation via microservices + RBAC and Kubernetes resource management; scaled to ~1M daily requests
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