Ashish Kumar Sahoo

Architected and implemented a serverless offloading mechanism using AWS SNS and Lambda functions, reducing AI response times by 70% (from 8s to 2s) and optimizing resource utilization.

Boosted system capacity and concurrency by deploying a stateless Retrieval-Augmented Generation (RAG) API with FastAPI, ensuring secure document storage in AWS S3 for scalable data access.

Streamlined new project development and accelerated delivery by creating a reusable Node.js backend template, pre-configured with standard REST API routing, authentication, and database connections.

Designed and orchestrated complex, high-volume reward computation workflows using AWS Step Functions and Python, enhancing reliability and reducing database locks during critical daily settlements.

Ensured real-time data consistency across distributed platforms by developing webhook-based synchronization APIs with FastAPI, replacing inefficient polling with event-driven updates.

Enhanced backend stability and performance during traffic spikes by integrating Redis-based rate limiting and request debouncing, mitigating production API throttling issues.

Accelerated team engineering velocity by documenting API endpoints, standardizing cloud integration patterns, and mentoring 2 interns, fostering best practices and knowledge transfer.

Architected and scaled peer-to-peer payment processing by logically decoupling write-heavy transaction endpoints from read-heavy reporting services within a Python and Django backend, improving system throughput.

Reduced core API response times by 40% by implementing a read-through Redis caching layer and resolving critical N+1 query problems in SQLAlchemy, significantly decreasing Amazon RDS load.

Developed robust pricing analytics services using Pandas to aggregate and process large financial datasets, exposing critical business insights via FastAPI for enhanced reporting.

Optimized frontend load times by designing dedicated aggregation APIs, consolidating data from multiple services into single payloads for React and Next.js clients.

Enhanced data accessibility for 2,000+ digital assets by architecting an automated metadata indexing pipeline, leveraging background job queues for secure data aggregation in AWS S3.

Automated data gathering for internal teams by developing interactive analytics dashboards, providing clear visualization of asset ownership and performance metrics, eliminating manual efforts.

Maintained high data consistency across distributed environments by developing idempotent scheduled tasks, preventing duplicate records during automated SQL database synchronization.