Suhas Anindith Nama
Professional Summary
Software Engineer with 3+ years of experience building scalable backend services, APIs, and cloud-native applications in Java, Spring Boot, and AWS, alongside hands-on experience designing and deploying a production-oriented multi-agent GenAI application using LangChain, RAG pipelines, and LLM APIs. Delivered enterprise systems with 99.9% uptime through resilient API engineering, Redis caching, and database performance tuning, while independently architecting an AI resume-generation system that orchestrates specialized agents across a ChromaDB-backed RAG pipeline with OpenAI and Anthropic API integration. Comfortable across the full stack from Java microservices and PostgreSQL-backed services to Python/FastAPI-based AI applications with a consistent focus on reliability, performance, and shipping software that holds up in production. Known for translating requirements into working systems end-to-end, whether that's a distributed backend service or an LLM-powered application.
Technical Skills
Work Experience
- Architected 5 production-grade full-stack applications using React, Node.js, and AWS, delivering scalable and high-performance solutions aligned with client business requirements.
- Automated cloud infrastructure provisioning and deployment workflows, reducing deployment time by 70% across client environments
- Engineered GitOps-driven CI/CD pipelines with automated testing, monitoring, and rollback mechanisms across 15+ production releases, ensuring reliable and uninterrupted application delivery.
- Spearheaded accessibility-focused web application development with cross-functional teams, achieving WCAG 2.1 AA compliance and increasing overall user reach by 15%.
- Optimized backend scalability and system performance using microservices architecture, PostgreSQL, and Redis, improving application response efficiency by 40% across critical services.
- Developed 12+ microservices using Java Spring Boot and PostgreSQL, supporting high-volume enterprise applications with 99.9% system uptime.
- Enhanced backend data processing and API performance by implementing Redis caching and query tuning strategies, reducing average response time.
- Eliminated application scalability bottlenecks through performance tuning and root-cause analysis, improving overall system throughput by 3x across critical services.
- Coordinated cross-functional collaboration with frontend and backend teams to deliver full-stack features on schedule, accelerating feature delivery by 25%.
- Streamlined deployment workflows and testing pipelines using Jenkins, GitHub Actions, JUnit, and Mockito, reducing production incidents by 40%.
- Engineered backend components for enterprise-scale applications processing 1M+ daily transactions, strengthening API reliability and database performance.
- Optimized API workflows and backend processes for business-critical systems, enhancing application maintainability and operational stability across services.
- Diagnosed 50+ production issues through root-cause analysis and defect remediation using JIRA, reducing customer-reported bugs.
- Partnered with development and QA teams during Agile sprint cycles to support feature validation, ensuring stable and timely production releases.
- Automated regression and functional testing using Selenium and JUnit, increasing overall test coverage by 45% across core application modules.
Education
Certifications
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