Home

Naga Y - Senior Java Developer/ AI

[email protected]

Location: Jersey City, New Jersey, USA

Relocation: YEs

Visa: H1B

Sr. Java Full Stack Developer (Java + Python/AI Engineer) Name: Naga Y Mail Id: [email protected] Contact No: +1 6149830428 Professional Summary: Senior Full Stack Engineer with 10+ years building distributed, end-to-end products across design, implementation, testing, and deployment using Java (8/11/17), Spring Boot, and cloud-native architectures in financial services, insurance, healthcare, and banking domains, with a strong dual focus on Java (60%) and Python (40%) for backend services, automation, and scripting. Hands-on experience delivering microservices-based platforms handling high-volume transactional workflows, including licensing, compliance, and financial data processing. Strong backend expertise in Spring Boot, Spring MVC, Hibernate/JPA, designing APIs with proper validation, exception handling, and idempotent processing. Applied SOLID principles, J2EE design patterns (DAO, DTO, Singleton, Factory, MVC, Front Controller), and TDD practices with JUnit/Mockito to build scalable, maintainable, and loosely coupled enterprise applications. Built and supported event-driven systems using Apache Kafka and Amazon MQ, implementing retry logic, DLQs, and asynchronous processing patterns. Experience working with hybrid architectures combining Java, Node.js, and Python services for REST API orchestration, automation, AWS Lambda functions, and shell scripting in production data processing pipelines. Solid frontend exposure with React.js and Angular Experience with NoSQL and distributed SQL databases including Apache Cassandra, DynamoDB, MongoDB, and CockroachDB for high-write, time-series, and globally distributed transactional data patterns in insurance, healthcare, and financial services domains. Cloud experience across AWS (EC2, EKS, ECS, Lambda, S3, Aurora PostgreSQL, RDS, DynamoDB, API Gateway, SNS, SQS, MSK, IAM, Route 53, ELB, CloudWatch), supporting scalable and resilient distributed applications. Containerization and orchestration using Docker, Kubernetes, and Helm, handling deployments, scaling, and environment consistency. Experience migrating legacy applications to microservices and modern stacks, including Spring Boot upgrades and configuration refactoring. Strong experience with data pipelines, including ETL processing, batch ingestion, and near real-time streaming using Kafka and SQL-based systems. Worked on search and observability platforms using Elasticsearch, Splunk, and ELK Stack, supporting log analysis, metrics dashboards, alerting, and production debugging; experience extending this stack with Prometheus and Grafana for metrics collection, SLO monitoring, and operational visibility. Performance tuning at JVM and database level, handling memory issues, thread contention, slow queries, and connection pool optimizations. CI/CD pipeline implementation using GitLab CI, Jenkins, and GitHub Actions, automating build, test, and deployment workflows. Experience implementing security using OAuth 2.0, JWT, and Spring Security, securing APIs and enterprise integrations. Exposure to serverless and event-driven architectures using AWS Lambda, API Gateway, and messaging services. Built internal tools and automation services using Python, REST API back-ends, AWS Lambda functions, shell scripts, and test automation (pytest, unittest) following TDD practices, supporting operational workflows, data validation, and integration with no-SQL data stores. 2+ years of hands-on AI/ML experience building production LLM-powered applications using RAG architecture, LangChain, Spring AI, OpenAI/Azure OpenAI APIs, and vector databases (FAISS, pgvector); additionally applied ML-based anomaly detection (scikit-learn, AWS SageMaker) on high-volume financial and licensing data streams. Technical Skills: Languages Java (8/11/17), Python (3.x), Kotlin, JavaScript (ES6), TypeScript, Shell Scripting (Bash) Backend Core Java, J2EE, Spring Boot, Spring MVC, Spring Cloud, Spring Security, Hibernate/JPA, REST, GraphQL, Microservices, Python (Flask, FastAPI), J2EE Design Patterns (DAO, DTO, Singleton, Factory, MVC, Front Controller) Frontend React.js, Redux, Angular, TypeScript, HTML5, CSS3, Bootstrap Microservices & Messaging Apache Kafka, AWS Managed Streaming for Apache Kafka (MSK), Amazon MQ, AWS SNS, AWS SQS, RabbitMQ Cloud (AWS) EC2, EKS, ECS, Lambda, S3, Amazon Aurora PostgreSQL, RDS, DynamoDB, API Gateway, SNS, SQS, MSK, IAM, Route 53, ELB, CloudWatch, CloudFormation Containers & Orchestration Docker, Kubernetes, Helm Databases MySQL, PostgreSQL, Amazon Aurora PostgreSQL, Oracle, MongoDB, DynamoDB, Apache Cassandra, CockroachDB Search & Logging Splunk, Prometheus, Grafana, Elasticsearch, ELK Stack, CloudWatch, Datadog DevOps & CI/CD Jenkins, GitLab CI, GitHub Actions, Maven, Gradle, Terraform, Ansible, Helm Testing JUnit, Mockito, TestNG, pytest, unittest, Mocha, Chai, TDD, BDD, Postman, SonarQube Security OAuth 2.0, JWT, TLS Tools & IDEs IntelliJ IDEA, VS Code, Eclipse, Postman, Swagger, JIRA, Confluence, Git, GitHub, GitLab, Bitbucket AI / Data LLMs (GPT-4, Azure OpenAI), LangChain, Spring AI, RAG, FAISS, pgvector, scikit-learn, AWS SageMaker, Python ML utilities, vector search pipelines, GitHub Copilot, Amazon Q Developer Methodologies Agile/Scrum, Kanban, CI/CD, TDD, Microservices Architecture, End-to-End Product Ownership (Design Build Test Deploy) Professional Experience: Client: National Insurance Producer Registry Jan 2024 Present Role: Sr. Java Full Stack Developer (AI Focused) Responsibilities: Delivered distributed backend services using Java (11/17), Spring Boot, and Spring MVC, exposing REST and GraphQL APIs supporting multi-state insurance licensing, renewals, and compliance workflows with strict data validation and transactional consistency. API integrations across external state systems and internal platforms, handling XML/JSON transformations, idempotent processing, and request validation using Postman and automated test suites. React-based UI flows for eligibility validation, appointment renewals, and compliance checks enhanced by optimizing API interaction patterns, reducing redundant network calls, and improving frontend responsiveness. Root cause analysis of production defects impacting financial transactions; traced data inconsistencies across Kubernetes-hosted microservices, corrected validation layers, and stabilized downstream fee calculation logic. Backend automation and data-processing utilities built using Python, supporting operational workflows, validation pipelines, and near real-time data transformations. Automated provisioning and lifecycle management of VM instances (creation, scaling, monitoring) in a private cloud environment leveraging OpenStack-based infrastructure, enabling efficient deployment of Spring Boot microservices Migration of legacy services into AWS, including containerization using Docker, orchestration via Kubernetes and Helm, and CI/CD automation through GitLab CI pipelines for consistent multi-environment deployments. Decomposition of monolithic eligibility processing into domain-specific microservices (Resident / Non-Resident), improving isolation, deployment independence, and system resilience under peak loads. Event-driven workflows powered by Apache Kafka, including producers/consumers for licensing and compliance events, enabling asynchronous processing and decoupling between services. Data integrity enforcement using Kafka retry strategies, dead-letter topics, and validation layers to ensure reliability of regulatory data exchange with external state systems. Optimization of ETL pipelines handling regulatory datasets across Amazon Aurora PostgreSQL, CockroachDB, and DynamoDB using query tuning, partitioning, indexing strategies, and Python-based batch processing improvements; designed schemas leveraging CockroachDB's distributed SQL capabilities for horizontally scalable, multi-region transactional workloads. Modernization of legacy Spring applications to Spring Boot with Kotlin, replacing XML configurations with annotation-based setups and leveraging Kotlin features for null safety and reduced boilerplate. Real-time activation workflows leveraging Kafka events processed through Python services, applying business rules and exposing APIs driving frontend state transitions. CI/CD pipelines standardized for Java, frontend, and Node.js components using GitLab CI, automating build, test, and deployment workflows across environments. Observability and monitoring handled via Splunk, ELK Stack, and application-level logging; supported production debugging involving log ingestion, indexing, and query latency. Cloud infrastructure support across AWS EC2, Auto Scaling, Lambda, S3, SNS/SQS, DynamoDB/RDS, and CloudFormation, EKS, Amazon Aurora PostgreSQL, MSK (Managed Streaming for Apache Kafka), API Gateway, IAM, Route 53, and ELB, enabling scalable, highly available, and event-driven backend systems with infrastructure provisioned through Terraform. Secure API access using OAuth 2.0 and Spring Security, integrating with enterprise identity providers for token-based authentication and authorization. AI-powered internal assistant built using LLM-based retrieval-augmented generation (RAG) architecture with OpenAI GPT-4 / Azure OpenAI, integrating backend Spring Boot APIs, FAISS/pgvector vector stores, and Redis caching layers to support compliance Q&A and operational knowledge retrieval at NIPR (2+ years). Designed and deployed Generative AI pipelines using LangChain and Spring AI frameworks for intelligent document processing and regulatory data summarization, reducing manual review effort across multi-state insurance licensing workflows. Implemented AI-driven anomaly detection on licensing transaction streams using Python-based ML models integrated into Kafka consumer pipelines, flagging data inconsistencies and compliance violations in near real time; leveraged scikit-learn and AWS SageMaker for model training and inference endpoints. Code quality and testing enforced through JUnit, Mockito, SonarQube, along with static analysis and automated test coverage in CI pipelines. Developer productivity improved using GitHub Copilot and Amazon Q Developer for code generation, test scaffolding, and debugging within IntelliJ and VS Code environments. Environment: Java (11/17), Python 3, Kotlin, Spring Boot, Spring MVC, REST APIs, GraphQL, React, Angular, Node.js, MySQL, Amazon Aurora PostgreSQL, CockroachDB, DynamoDB, Apache Kafka, AWS MSK, Elasticsearch, Docker, Kubernetes (EKS), Helm, Terraform, AWS (EC2, Lambda, S3, API Gateway, SNS, SQS, IAM, Route 53, ELB, CloudWatch, CloudFormation), GitLab CI, Jenkins, GitHub Actions, Splunk, Prometheus, Grafana, ELK Stack, Redis, JUnit, Mockito, pytest, TDD, SonarQube, OAuth 2.0, Spring Security, J2EE Design Patterns, Agile/Scrum, Jira, Git, OpenAI GPT-4, Azure OpenAI, LangChain, Spring AI, FAISS, pgvector, scikit-learn, AWS SageMaker, LLM/RAG Client: ResMed - San Diego, CA. Jun 2022 Dec 2023 Role: Sr. Java Full Stack Developer Responsibilities: Delivered microservices using Java 11/17, Spring Boot, and Spring MVC exposing REST and GraphQL APIs for high-volume device telemetry and analytics workloads across distributed systems Built backend services supporting React + TypeScript dashboards, enabling near real-time visibility into device operations, system health, and automation workflows Introduced Node.js middleware layer for API orchestration, response aggregation, and lightweight integrations between frontend applications and backend microservices Integrated Python-based AWS Lambda services via API Gateway, enabling operational control features, audit tracking, and manual override capabilities within dashboard applications Stabilized a high-throughput ingestion pipeline by introducing asynchronous processing, message batching, and back-pressure handling using Amazon MQ, eliminating system failures during traffic bursts Transitioned legacy messaging from TIBCO EMS to Amazon MQ, restructuring producers/consumers with idempotent processing, retry logic, and dead-letter queue (DLQ) handling Investigated JVM-level performance bottlenecks using heap dumps, thread analysis, and Datadog metrics, resolving GC pauses, memory leaks, and thread contention in production Replaced relational scaling bottlenecks with Cassandra clusters, achieving linear write scalability and predictable read performance for historical device analytics dashboards. Tuned JVM configurations, connection pools, and thread pools to sustain consistent low-latency processing under large payload and concurrent traffic scenarios Deployed and managed applications on OpenStack private cloud environments, leveraging core services like Nova (compute), Neutron (networking), and Cinder (block storage) Used OpenStack REST APIs and CLI to provision and manage virtual machines, volumes, and networking resources Configured Neutron networking components including subnets, routers, floating IPs, and security groups for application isolation Managed VM lifecycle operations (boot, resize, snapshot, terminate) using OpenStack Horizon dashboard and CLI Implemented role-based access control (RBAC) using Keystone for secure multi-tenant environments Worked with Glance to manage and upload VM images for application deployment Addressed AWS ECS/Fargate startup delays and RDS connection saturation through task-level tuning, connection pooling strategies, and CloudWatch-based monitoring and alerting Implemented cost-control automation using AWS Lambda and Terraform, scheduling non-critical workloads and exposing control operations through a lightweight Node.js + React dashboard Defined infrastructure using Terraform, provisioning EC2 Auto Scaling, IAM roles, networking, and security configurations for multi-environment deployments Built serverless workflows using AWS Lambda (Node.js/Python) integrated with API Gateway, supporting event-driven automation and internal platform services Enabled resilient data pipelines using Lambda triggers on S3, queues, and streams with retry strategies, DLQs, and operational monitoring via CloudWatch Optimized Lambda performance by tuning memory allocation, timeouts, and concurrency limits, ensuring stable execution across high-load scenarios Automated container deployments using Linux shell scripting and Docker, integrating with AWS ECS for streamlined release cycles Orchestrated AWS resources using Python (boto3) for automated lifecycle operations across EC2, ECS, and RDS environments Containerized Spring Boot services using Docker and validated deployments through local environment setups connected to AWS test infrastructure for end-to-end verification Remediated security vulnerabilities identified through Mend scans, upgrading dependencies and rebuilding services to address high-severity CVEs Improved MongoDB query performance by introducing compound indexing, optimizing queries, and upgrading drivers to eliminate full collection scans Migrated repositories from Bitbucket to GitHub and artifacts from Nexus to JFrog Artifactory, aligning CI/CD pipelines with standardized tooling Upgraded services to Java 17 and latest Spring Boot versions, validating changes through JUnit and integration testing Built transformation services to convert proprietary device data into FHIR-compliant formats, supporting healthcare interoperability and downstream analytics Enforced platform security using TLS, IAM roles, OAuth2/JWT, and audit logging aligned with healthcare compliance requirements Integrated Elasticsearch (ELK stack) for centralized logging, enabling real-time observability across microservices and ingestion pipelines Applied event-driven architecture, caching strategies, and asynchronous communication patterns to handle traffic spikes without service disruption Supported deployments across AWS ECS, EKS, EC2, RDS, DynamoDB, ensuring scalability, observability, and operational stability in cloud-native environments Environment: Java 11/17, Spring Boot, Spring MVC, Hibernate, REST, GraphQL, MongoDB, Amazon MQ, Docker, Terraform, AWS (ECS, EKS, EC2, RDS, Lambda, DynamoDB, CloudWatch, API Gateway), Node.js, React, Python, Datadog, Elasticsearch, GitHub, JFrog Artifactory, Maven, JUnit, Client: TD Bank Cherry Hill, NJ. Jan 2021 Nov 2021 Role: Java Full Stack Developer Responsibilities: Backend services built using Java 8, Spring Boot, and Spring MVC, exposing RESTful APIs consumed by React-based UI and downstream banking systems. Microservices ecosystem structured around Spring Boot with inter-service communication handled through REST and asynchronous messaging using Apache Kafka for transaction events and notifications. API layer included request validation, exception handling, and response transformation (JSON/XML), with endpoint testing and debugging through Postman. Data persistence handled via Hibernate/JPA, including complex entity relationships and optimized queries against relational databases supporting transactional workloads. MongoDB used for storing semi-structured claims and audit-related data, enabling flexible schema handling and analytical queries for reporting use cases. Frontend modules built with React.js, JavaScript (ES6), HTML5, CSS3, and Bootstrap, creating reusable components and integrating seamlessly with backend APIs. Application state managed using Redux, with integration of both REST and GraphQL APIs to support dynamic UI data requirements. Unit and integration test coverage ensured through JUnit and Mockito for backend services, along with frontend validation using Mocha and Chai. Containerized services using Docker, enabling consistent runtime environments across development, QA, and production stages. Integrated Cassandra with Kafka streams for fraud scoring output persistence, achieving sub-20ms writes at peak volumes. CI/CD workflows maintained using Maven and Jenkins, automating build pipelines, test execution, and deployment processes. Code quality checks performed via SonarQube, addressing vulnerabilities, code smells, and maintainability concerns prior to releases. AWS environment support included provisioning and managing EC2, configuring Auto Scaling, handling Elastic IPs, and monitoring system health through CloudWatch. Serverless integrations implemented using AWS Lambda (Node.js), processing event-driven data flows with S3 and SNS for notifications and asynchronous processing. Agile delivery tracked using JIRA, collaborating with product owners, QA teams, and other developers to manage user stories, defects, and release cycles. Environment: Java 8, Spring Boot, Spring MVC, Hibernate/JPA, REST APIs, GraphQL, Apache Kafka, MongoDB, React.js, Redux, JavaScript (ES6), HTML5, CSS3, Bootstrap, Docker, AWS (EC2, Lambda, S3, SNS, CloudWatch), Maven, Jenkins, Git, JUnit, Mockito, Mocha, Chai, SonarQube, JIRA. Client: Majesco Mumbai, India. Apr 2017 - Dec 2019 Role: Java Full Stack Developer Responsibilities: Backend services structured using Java, Spring Boot, and layered architecture to support policy issuance, endorsements, and claims workflows REST APIs designed for seamless communication across internal modules and external insurance systems using Spring MVC and JSON payloads Complex data handling implemented using Hibernate/JPA with optimized queries; exposure to both relational databases and MongoDB for semi-structured data UI modules built with Angular and TypeScript, enabling dynamic form handling, validations, and real-time user interactions for policy management screens API integration between frontend and backend ensured smooth data flow, handling edge cases like validation failures and partial updates Event-driven communication introduced using Apache Kafka to decouple services and support asynchronous processing for notifications and policy updates Cloud deployment exposure on AWS (EC2, S3, RDS) including environment setup, application monitoring, and basic troubleshooting Build and release processes handled using Jenkins pipelines and Maven, supporting continuous integration workflows Version control and collaboration maintained using Git, managing feature branches, merges, and code reviews Unit testing performed using JUnit, ensuring stability of business logic and reducing regression issues during releases Participation in Agile/Scrum ceremonies, including sprint planning, backlog grooming, and daily stand-ups in coordination with cross-functional teams Environment: Java, Spring Boot, Spring MVC, Hibernate, JPA, REST APIs, Angular, TypeScript, HTML, CSS, Bootstrap, MongoDB, Apache Kafka, AWS (EC2, S3, RDS), Jenkins, Maven, Git, JUnit, Agile (Scrum). Client: Sasken Technologies Bangalore, India. Jul 2015 - Mar 2017 Role: Java Developer Responsibilities: Built backend modules using Java and Spring Framework (Core, MVC) to support telecom service workflows and device data processing Designed and exposed RESTful APIs with JSON payloads for integration with frontend applications and third-party systems Handled relational data operations using Spring Data JPA with PostgreSQL, including schema updates and query optimization for transactional data Contributed to UI enhancements using HTML, CSS, JavaScript, and jQuery, improving usability of internal monitoring dashboards Deployed applications on WebLogic Server, including environment configuration, application packaging, and troubleshooting deployment issues Managed build and dependency lifecycle using Maven, ensuring consistent builds across development and QA environments Used GitHub for version control, branch management, and collaboration during feature development and bug fixes Integrated RabbitMQ for asynchronous processing of background jobs such as event notifications and data synchronization Created and executed unit test cases using JUnit, supporting QA cycles and reducing regression defects Worked closely with QA and business teams to analyze defects, reproduce issues, and deliver timely fixes Participated in Agile (Kanban) ceremonies, including backlog refinement and continuous delivery of incremental features Supported production issues by analyzing logs, identifying root causes, and applying fixes with minimal downtime Environment: Java, Spring (Core, MVC), REST APIs, JSON, PostgreSQL, HTML, CSS, JavaScript, jQuery, WebLogic, RabbitMQ, Maven, GitHub, JUnit, Agile (Kanban). Keywords: continuous integration continuous deployment quality analyst artificial intelligence machine learning user interface message queue javascript sthree green card California Idaho New Jersey