Java Full-Stack Developer with AI Expertise

Nagendra Babu Surineni

Java Full Stack Developer

USA Open for Relocation *****************@*****.*** +1-469-***-**** SUMMARY

Java Full Stack Developer AI with 5+ years of experience designing and delivering high-performance, cloud-native enterprise applications in fintech and SaaS environments. Strong expertise in Java 17, Spring Boot microservices, React, Angular, and distributed systems architecture, with added proficiency in AI tools for predictive analytics and intelligent automation. Experienced in building secure RESTful and GraphQL APIs, implementing CI/CD pipelines, deploying containerized applications to AWS and Azure Kubernetes Service (AKS), and integrating AI-driven features for enhanced decision-making. Proven track record of improving system scalability, performance, and deployment efficiency in Agile environments, now leveraging AI for optimized workflows and user experiences. SKILLS

Programming Languages: Java (8/11/17), Kotlin, JavaScript (ES6+), TypeScript, Python (for AI integrations) Backend Technologies: Spring Boot, Spring Cloud, Spring Security, Hibernate, JPA, Microservices Architecture, RESTful APIs, GraphQL (DGS), gRPC

Frontend Technologies: React.js (Hooks, Redux), Angular (13+), HTML5, CSS3, Bootstrap, Material UI Cloud & DevOps: Microsoft Azure, Azure Kubernetes Service (AKS), AWS (EC2, S3, Lambda), Docker, Kubernetes, Azure DevOps, Jenkins, GitHub Actions, CI/CD Pipelines

Databases & Caching: PostgreSQL, MySQL, MongoDB, Redis Testing & Quality: JUnit, Mockito, Karate, Cypress, Jest, Enzyme, JMeter AI Tools & Skills: TensorFlow, PyTorch, Azure AI, Machine Learning, Natural Language Processing (NLP), Predictive Analytics, AI Model Deployment

Architecture & Practices: Domain-Driven Design (DDD), Event-Driven Architecture, CQRS, OAuth2, OpenID Connect, Secure API Design, Agile/Scrum

Tools: Git, IntelliJ IDEA, VS Code, Jira, Confluence, SonarQube EXPERIENCE

Goldman Sachs, USA Jul 2023 – Present

Java Full Stack Developer

Designed and developed 15+ Spring Boot microservices (Java 17, Kotlin) supporting core banking modules including Accounts, Transactions, Money Movement, and Document Processing, integrating AI-driven predictive analytics using TensorFlow for fraud detection and risk assessment.

Built secure RESTful and GraphQL APIs (DGS framework) enabling seamless integration between backend systems and Angular-based frontend applications, with NLP capabilities via Azure AI for intelligent document processing and chatbots.

Improved API response time by 30% through Redis caching implementation and optimized database queries in PostgreSQL, enhanced by AI-powered query optimization using PyTorch models.

Integrated third-party systems (FIS Core Banking, Okta SSO, Giact identity verification, fraud analytics platforms) using secure gRPC and REST integrations, incorporating Machine Learning algorithms for real-time anomaly detection.

Implemented OAuth2 and OpenID Connect authentication flows to enhance application security and regulatory compliance, with AI-enhanced security monitoring for threat prediction.

Containerized microservices using Docker and deployed to Azure Kubernetes Service (AKS), enabling zero- downtime deployments and horizontal scaling, supported by AI model deployment pipelines for automated scaling based on predictive load forecasting.

Automated CI/CD pipelines using Azure DevOps, reducing deployment time by 40% and increasing release frequency, with AI tools integrated for intelligent test automation and defect prediction.

Conducted performance testing with JMeter and API automation using Karate, increasing test coverage to 85%+, leveraging AI for predictive performance analytics.

Participated in Agile/Scrum ceremonies including sprint planning, backlog grooming, and retrospectives to ensure timely delivery, incorporating AI-driven sprint planning tools for resource optimization.

Environment: Java 17, Kotlin, Spring Boot, Spring Cloud, GraphQL (DGS), REST, gRPC, Redis, PostgreSQL, Angular, Docker, AKS, Azure DevOps, JMeter, Karate, TensorFlow, PyTorch, Azure AI, NLP Adobe Mar 2019 – Jul 2021

Java Full Stack Developer

Developed scalable Spring Boot microservices exposing RESTful APIs consumed by React.js and mobile applications, integrating Machine Learning models via TensorFlow for personalized user recommendations and content optimization.

Built reusable and modular React components using Hooks and Redux, improving UI maintainability and reducing code duplication by 25%, with AI-enhanced UX features like predictive search using NLP from Azure AI.

Implemented OAuth2-based authentication and authorization using Spring Security and OpenID Connect, fortified by AI-driven behavioral analysis for anomaly detection in user access patterns.

Deployed backend services to AWS (EC2, S3) with automated CI/CD pipelines, reducing manual deployment effort by 35%, and incorporated AI model deployment for automated scaling and predictive maintenance.

Improved frontend performance through lazy loading, code splitting, and optimized rendering techniques, reducing page load time by 20%, supported by AI analytics for real-time performance tuning.

Increased backend reliability through JUnit and Mockito unit testing; achieved 80%+ code coverage, with AI tools assisting in automated test case generation and defect prediction.

Conducted cross-browser compatibility testing and ensured responsive design implementation using Material UI and modern CSS practices, enhanced by AI for adaptive UI personalization.

Collaborated with UX designers, QA teams, and product managers in Agile development cycles to deliver high-quality releases, leveraging AI for collaborative insights and project forecasting.

Environment: Java, Spring Boot, React.js, Redux, REST APIs, AWS (EC2, S3), PostgreSQL, Material UI, Jest, Enzyme, JUnit, Git, Jira, TensorFlow, Azure AI, NLP. EDUCATION

Master’s in computer science, University of Houston, Clear Lake, TX

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