Backend Software Engineer - Java, Microservices, AWS

RAHUL ANKOSHKAR

Gainesville, FL +1-352-***-**** *********@*****.*** LinkedIn GitHub

SUMMARY

Backend Software Engineer with 4+ years of experience building scalable, secure, and cloud-based backend systems in fintech and enterprise environments. Strong expertise in Java, Spring Boot, microservices, and AWS. Proven track record of improving system performance, reducing latency, and increasing deployment efficiency through optimized backend architecture and automation. Experienced in designing high- throughput APIs, distributed systems, and event-driven applications with production-level reliability. PROFESSIONAL EXPERIENCE

Backend Software Engineer JPMorgan Chase & Co. – United states Jan 2025 – Present

• Designed and developed microservices using Java 17 and Spring Boot to support core banking and transaction processing systems handling high-volume financial operations.

• Built and maintained secure REST APIs for payments and account workflows, implementing validation, error handling, and API versioning, improving system reliability.

• Implemented event-driven architecture using Kafka, enabling asynchronous processing and improving system throughput and fault tolerance.

• Deployed cloud-native applications on AWS (EC2, RDS, S3, Lambda) with auto-scaling and load balancing, ensuring high availability and scalability.

• Improved deployment speed by 40% by building CI/CD pipelines using Jenkins and GitHub Actions, reducing manual release effort.

• Reduced API latency by 30% through database query optimization, indexing, and caching using Redis.

• Strengthened system resilience by implementing circuit breaker patterns (Resilience4j) and improving failure handling in distributed services.

• Enhanced observability using centralized logging, monitoring (CloudWatch), and metrics tracking, enabling faster issue detection and resolution.

• Supported production systems through on-call rotation, incident resolution, and root cause analysis (RCA) to maintain system uptime.

Software Engineer Streebo – India Jan 2020 – Dec 2022

• Developed backend services using Java and Spring Boot for enterprise chatbot and automation platforms used by large-scale clients.

• Designed and built REST APIs to integrate AI/NLP systems with enterprise applications, improving workflow automation efficiency.

• Migrated legacy monolithic applications to microservices architecture, improving scalability and reducing deployment dependencies.

• Improved system performance by 25% through optimized SQL queries, JPA configurations, and caching strategies using Redis.

• Built backend systems supporting high concurrent user interactions, ensuring stability under increased traffic loads.

• Supported AWS-based deployments, including service configuration, monitoring, and scaling.

• Collaborated with cross-functional teams (AI, frontend, DevOps) to deliver end-to-end features in Agile environments. TECHNICAL SKILLS

• Programming: Java (8/11/17), Python, SQL, JavaScript

• Backend: Spring Boot, Spring MVC, Hibernate, JPA, REST APIs

• Architecture: Microservices, Distributed Systems, Event-Driven Architecture, API Design, Resilience Patterns, Circuit Breaker

• Cloud & DevOps: AWS (EC2, RDS, S3, Lambda, IAM, Auto Scaling), Docker, Kubernetes, Jenkins, GitHub Actions, CI/CD

• Databases: MySQL, PostgreSQL, Oracle, MongoDB, Redis

• Messaging: Kafka

• Security: Spring Security, JWT, OAuth2, RBAC

• Testing: JUnit, Mockito, Integration Testing

• Observability: Logging, Monitoring (CloudWatch), Metrics PROJECTS

Backend Integrated Machine Learning Services

• Built scalable backend services to expose machine learning models via REST APIs for real-time inference.

• Integrated Python-based ML models (Scikit-learn) into backend workflows, enabling automated decision-making.

• Implemented API versioning, validation, and standardized error handling to improve API reliability.

• Improved response time by optimizing request handling and backend processing logic. IoT Cloud Data Processing Platform

• Designed event-driven backend pipeline using AWS IoT Core, Lambda, and EventBridge for real-time sensor data processing.

• Built scalable services to process high-volume streaming data with fault-tolerant architecture.

• Developed APIs and dashboards for monitoring system performance and data flow.

• Ensured system reliability through distributed processing and cloud-native patterns. EDUCATION

Master of Science in Computer Science University of Florida, Gainesville, FL Jan 2023 – Dec 2024

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