Java Full Stack Developer

Position: Java Full Stack DeveloperLocation: *** REMOTE***Duration: 1 YearPosition Summary9+ years of experience in large scale distributed system development including hands on operational experience5+ Hands on experience with Java, Spring boot, Kafka, AngularJS/ReactJS, NoSQL Database, Redis, Docker/Kubernetes, GitHub3+ Experience working with Microservices and Event driven architecture like Kafka2+ experience on Cloud environment and architectures, preferably Azure1+ experience with AI development using Agentic AI, Chatbot and Gen AIProven experience with full development life cycle for large-scale software products including extensive experience with service-oriented architectures, design patterns and web servicesUnderstand and implement CI/CD deployment pipelines with JPAC/Github Actions.Strong knowledge in performance, scalability, distributed architecture, and engineering best practicesLeverage knowledge of internal and industry prior knowledge in design decisionsIn-depth knowledge of system programming, Deep understanding of system performance tradeoffs, load balancing, and engineering for high availabilityUnderstand Product / Project / Consumer priorities and follow Agile methodologies to deliver features within time.Creation/involvement in documented designs following agreed to design patterns and standards.Perform Coding and unit testing independently and assist/mentor his team members whenever required.Adherence to coding standardsCommunicate effectively with other engineers/ QE and onshore teamSupport the QE team during testing via defect fixes, code deployment, clarificationsFully encourage and facilitate high quality code through of support QE team efforts including but not limited to mentoring, assistance, and writing/executing automation tests as needed. All contractor resources are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of their day-to-day responsibilities. This includes, but is not limited to:Consistent Use: Maintain a minimum of 90% weekly usage of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise.Applied Productivity: Leverage AI tools to enhance coding, documentation, data analysis, and decision-making workflows.Continuous Learning: Stay current with evolving AI capabilities and features, and apply them to improve delivery quality and velocity.