Venkatamohan Potturu

About Venkatamohan Potturu

I design and build high-performance, scalable microservices platforms for financial and retail systems.I’m a Java Full Stack Engineer with 4+ years of experience developing low-latency, cloud-native applications using Java 17, Spring Boot, and modern frontend frameworks. Currently working on merchant settlement platforms at American Express, I specialize in distributed systems, event-driven architectures, and performance optimization for high-volume transaction systems.What I focus on:• Designing resilient microservices using Spring Boot• Building event-driven systems with Kafka & RabbitMQ• Developing low-latency APIs with PostgreSQL & Redis• Implementing scalable cloud infrastructure on AWS• Applying strong DSA & System Design principles to real-world systemsImpact delivered:• Reduced settlement reconciliation from T+2 to T+0 for priority merchants• Improved backend throughput by 28% using concurrency optimization• Reduced API latency from 480ms to 290ms through caching and indexing• Saved ~$75K annually through cloud migration and optimization• Improved production observability and incident detection by 35%I enjoy solving complex backend challenges, optimizing distributed systems, and building platforms that scale reliably under peak load conditions.Open to Backend Engineer, Full Stack Engineer, and Distributed Systems roles.

Experience

1. Full-stack Developer

   American Express

   Apr 2025 — Present · US

   Designed and enhanced a high-throughput merchant settlement platform using Java 17 and Spring Boot, implementing idempotent REST APIs and saga-based orchestration to enable reliable same-day (T+0) settlement cycles.• Developed low-latency validation and reconciliation services using Spring Boot, JPA (Hibernate), and PostgreSQL, sustaining sub-120ms response times under peak transaction loads.• Applied distributed system resiliency patterns using Resilience4j (circuit breaker, rate limiter, bulkhead) to improve fault tolerance and prevent cascading failures across services.• Optimized large-scale reconciliation processing pipelines handling 250K+ settlement records per batch by leveraging advanced data structures and algorithmic improvements, reducing imbalance detection time by over 65%.• Built secure internal financial dashboards using Angular and Spring MVC, enabling real-time operational visibility for 300+ finance stakeholders.• Provisioned and managed AWS infrastructure using Terraform (Infrastructure as Code), including ECS, RDS, VPC, and IAM, significantly improving deployment consistency and reducing provisioning time.• Collaborated cross-functionally with Data Science teams to implement an AI-powered financial assistant using a RAG-based architecture with vector embeddings and controlled document retrieval across governed datasets.

Education

• Lovely Professional University

  Bachelor's degree, computer science and engineering

  2019 — 2023

• University of Missouri-Kansas City

  Master's degree, Computer Science