Sr Full stack Java Developer

AI Full Stack Java Developer

• Designed and developed scalableAI-powered full-stack applications using Java, Spring Boot, React/Angular, REST APIs, and cloud-native technologies.

• IntegratedGenerative AI and Large Language Models (LLMs) into enterprise applications to deliver intelligent search, content generation, recommendation, summarization, and conversational capabilities.

• Built AI-enabled backend services usingJava, Spring Boot, Spring AI, LangChain/LangGraph concepts, and RESTful APIs, ensuring secure and maintainable application architecture.

• DevelopedRetrieval-Augmented Generation (RAG) solutions by integrating LLMs with enterprise documents, knowledge bases, vector databases, and semantic search.

• Implementedprompt engineering, prompt templates, response validation, context management, and AI guardrails to improve accuracy, consistency, and reliability of AI-generated responses.

• Developed responsive and reusable frontend components usingReact/Angular, TypeScript, JavaScript, HTML5, and CSS3, integrating them with AI-enabled backend services.

• Designed microservices usingSpring Boot, Spring Cloud, API Gateway, and service-to-service communication for highly scalable distributed applications.

• Developed and consumedREST and event-driven APIs, integrating third-party AI platforms, enterprise systems, databases, and external services.

• Worked withOpenAI/Azure OpenAI or equivalent LLM platforms, embedding models, vector search, and AI APIs into production applications.

• Implemented vector-based knowledge retrieval using technologies such asPinecone, Azure AI Search, Elasticsearch, or PostgreSQL with pgvector.

• Designed data persistence solutions usingPostgreSQL, MySQL, MongoDB, and Redis, selecting appropriate storage mechanisms based on application requirements.

• AppliedSpring Security, OAuth 2.0, JWT, RBAC, and API security practices to protect enterprise and AI-powered applications.

• Implemented asynchronous and event-driven processing usingKafka, RabbitMQ, or cloud messaging services for high-volume workloads.

• Containerized applications usingDocker and deployed microservices toKubernetes and cloud platforms such as AWS, Azure, or GCP.

• Developed CI/CD pipelines usingJenkins, Maven, Git, GitHub/GitLab, and automated deployment workflows.

• Implemented automated unit, integration, API, and end-to-end testing usingJUnit, Mockito, REST Assured, Selenium, Playwright, or Cypress.

• Added observability throughlogging, metrics, distributed tracing, health checks, and application monitoring, helping identify performance and AI-service issues.

• Optimized application performance throughcaching, database tuning, API optimization, asynchronous processing, and efficient LLM/API utilization.

• Collaborated with product managers, architects, data scientists, QA engineers, and DevOps teams to transform business requirements into production-ready AI solutions.

Requirements

• 5+ years of professional software development experience with strong expertise inJava and Spring Boot.

• Strong hands-on experience buildingfull-stack applications using Java, Spring Boot, REST APIs, React or Angular, JavaScript, and TypeScript.

• Experience designing and developingmicroservices-based, scalable, and cloud-native applications.

• Practical experience integratingGenerative AI, Large Language Models (LLMs), and AI APIs into enterprise applications.

• Strong understanding ofRAG architecture, embeddings, vector databases, semantic search, prompt engineering, and LLM orchestration.

• Experience working withOpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar AI platforms.

• Knowledge ofSpring AI, LangChain/LangGraph, or comparable AI application frameworks is highly desirable.

• Experience developing and consumingRESTful APIs, JSON-based services, and third-party integrations.

• Strong database experience withPostgreSQL, MySQL, MongoDB, Redis, or similar technologies.

• Experience withKafka, RabbitMQ, or other event-driven messaging platforms.

• Hands-on experience withDocker, Kubernetes, CI/CD, Jenkins, Maven, Git, and cloud deployment.