{"schemaVersion":"jobsearcher.job.v1","id":"b2d9531941e91edebc32c2ed","url":"https://jobsearcher.com/jobs/b2d9531941e91edebc32c2ed","canonicalUrl":"https://jobsearcher.com/jobs/b2d9531941e91edebc32c2ed","title":"Sr Full stack Java Developer","description":"AI Full Stack Java Developer\nDesigned and developed scalable AI-powered full-stack applications using Java, Spring Boot, React/Angular, REST APIs, and cloud-native technologies.\nIntegrated Generative AI and Large Language Models (LLMs) into enterprise applications to deliver intelligent search, content generation, recommendation, summarization, and conversational capabilities.\nBuilt AI-enabled backend services using Java, Spring Boot, Spring AI, LangChain/LangGraph concepts, and RESTful APIs, ensuring secure and maintainable application architecture.\nDeveloped Retrieval-Augmented Generation (RAG) solutions by integrating LLMs with enterprise documents, knowledge bases, vector databases, and semantic search.\nImplemented prompt engineering, prompt templates, response validation, context management, and AI guardrails to improve accuracy, consistency, and reliability of AI-generated responses.\nDeveloped responsive and reusable frontend components using React/Angular, TypeScript, JavaScript, HTML5, and CSS3, integrating them with AI-enabled backend services.\nDesigned microservices using Spring Boot, Spring Cloud, API Gateway, and service-to-service communication for highly scalable distributed applications.\nDeveloped and consumed REST and event-driven APIs, integrating third-party AI platforms, enterprise systems, databases, and external services.\nWorked with OpenAI/Azure OpenAI or equivalent LLM platforms, embedding models, vector search, and AI APIs into production applications.\nImplemented vector-based knowledge retrieval using technologies such as Pinecone, Azure AI Search, Elasticsearch, or PostgreSQL with pgvector.\nDesigned data persistence solutions using PostgreSQL, MySQL, MongoDB, and Redis, selecting appropriate storage mechanisms based on application requirements.\nApplied Spring Security, OAuth 2.0, JWT, RBAC, and API security practices to protect enterprise and AI-powered applications.\nImplemented asynchronous and event-driven processing using Kafka, RabbitMQ, or cloud messaging services for high-volume workloads.\nContainerized applications using Docker and deployed microservices to Kubernetes and cloud platforms such as AWS, Azure, or GCP.\nDeveloped CI/CD pipelines using Jenkins, Maven, Git, GitHub/GitLab, and automated deployment workflows.\nImplemented automated unit, integration, API, and end-to-end testing using JUnit, Mockito, REST Assured, Selenium, Playwright, or Cypress.\nAdded observability through logging, metrics, distributed tracing, health checks, and application monitoring, helping identify performance and AI-service issues.\nOptimized application performance through caching, database tuning, API optimization, asynchronous processing, and efficient LLM/API utilization.\nCollaborated with product managers, architects, data scientists, QA engineers, and DevOps teams to transform business requirements into production-ready AI solutions.\n\nRequirements\n5+ years of professional software development experience with strong expertise in Java and Spring Boot.\nStrong hands-on experience building full-stack applications using Java, Spring Boot, REST APIs, React or Angular, JavaScript, and TypeScript.\nExperience designing and developing microservices-based, scalable, and cloud-native applications.\nPractical experience integrating Generative AI, Large Language Models (LLMs), and AI APIs into enterprise applications.\nStrong understanding of RAG architecture, embeddings, vector databases, semantic search, prompt engineering, and LLM orchestration.\nExperience working with OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar AI platforms.\nKnowledge of Spring AI, LangChain/LangGraph, or comparable AI application frameworks is highly desirable.\nExperience developing and consuming RESTful APIs, JSON-based services, and third-party integrations.\nStrong database experience with PostgreSQL, MySQL, MongoDB, Redis, or similar technologies.\nExperience with Kafka, RabbitMQ, or other event-driven messaging platforms.\nHands-on experience with Docker, Kubernetes, CI/CD, Jenkins, Maven, Git, and cloud deployment.","company":"Hudson Manpower","rawCompany":"hudson manpower","city":"Albany","state":"NY","isRemote":false,"isActive":false,"createdAt":"2026-08-28T09:40:15.479Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1254.00","title":"Web Developers","slug":"web-developers"},{"code":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Sr Full stack Java Developer","description":"AI Full Stack Java Developer\nDesigned and developed scalable AI-powered full-stack applications using Java, Spring Boot, React/Angular, REST APIs, and cloud-native technologies.\nIntegrated Generative AI and Large Language Models (LLMs) into enterprise applications to deliver intelligent search, content generation, recommendation, summarization, and conversational capabilities.\nBuilt AI-enabled backend services using Java, Spring Boot, Spring AI, LangChain/LangGraph concepts, and RESTful APIs, ensuring secure and maintainable application architecture.\nDeveloped Retrieval-Augmented Generation (RAG) solutions by integrating LLMs with enterprise documents, knowledge bases, vector databases, and semantic search.\nImplemented prompt engineering, prompt templates, response validation, context management, and AI guardrails to improve accuracy, consistency, and reliability of AI-generated responses.\nDeveloped responsive and reusable frontend components using React/Angular, TypeScript, JavaScript, HTML5, and CSS3, integrating them with AI-enabled backend services.\nDesigned microservices using Spring Boot, Spring Cloud, API Gateway, and service-to-service communication for highly scalable distributed applications.\nDeveloped and consumed REST and event-driven APIs, integrating third-party AI platforms, enterprise systems, databases, and external services.\nWorked with OpenAI/Azure OpenAI or equivalent LLM platforms, embedding models, vector search, and AI APIs into production applications.\nImplemented vector-based knowledge retrieval using technologies such as Pinecone, Azure AI Search, Elasticsearch, or PostgreSQL with pgvector.\nDesigned data persistence solutions using PostgreSQL, MySQL, MongoDB, and Redis, selecting appropriate storage mechanisms based on application requirements.\nApplied Spring Security, OAuth 2.0, JWT, RBAC, and API security practices to protect enterprise and AI-powered applications.\nImplemented asynchronous and event-driven processing using Kafka, RabbitMQ, or cloud messaging services for high-volume workloads.\nContainerized applications using Docker and deployed microservices to Kubernetes and cloud platforms such as AWS, Azure, or GCP.\nDeveloped CI/CD pipelines using Jenkins, Maven, Git, GitHub/GitLab, and automated deployment workflows.\nImplemented automated unit, integration, API, and end-to-end testing using JUnit, Mockito, REST Assured, Selenium, Playwright, or Cypress.\nAdded observability through logging, metrics, distributed tracing, health checks, and application monitoring, helping identify performance and AI-service issues.\nOptimized application performance through caching, database tuning, API optimization, asynchronous processing, and efficient LLM/API utilization.\nCollaborated with product managers, architects, data scientists, QA engineers, and DevOps teams to transform business requirements into production-ready AI solutions.\n\nRequirements\n5+ years of professional software development experience with strong expertise in Java and Spring Boot.\nStrong hands-on experience building full-stack applications using Java, Spring Boot, REST APIs, React or Angular, JavaScript, and TypeScript.\nExperience designing and developing microservices-based, scalable, and cloud-native applications.\nPractical experience integrating Generative AI, Large Language Models (LLMs), and AI APIs into enterprise applications.\nStrong understanding of RAG architecture, embeddings, vector databases, semantic search, prompt engineering, and LLM orchestration.\nExperience working with OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar AI platforms.\nKnowledge of Spring AI, LangChain/LangGraph, or comparable AI application frameworks is highly desirable.\nExperience developing and consuming RESTful APIs, JSON-based services, and third-party integrations.\nStrong database experience with PostgreSQL, MySQL, MongoDB, Redis, or similar technologies.\nExperience with Kafka, RabbitMQ, or other event-driven messaging platforms.\nHands-on experience with Docker, Kubernetes, CI/CD, Jenkins, Maven, Git, and cloud deployment.","datePosted":"2026-08-28T09:40:15.479Z","dateModified":"2026-08-28T09:40:15.479Z","hiringOrganization":{"@type":"Organization","name":"Hudson Manpower","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Albany","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b2d9531941e91edebc32c2ed"},"url":"https://jobsearcher.com/jobs/b2d9531941e91edebc32c2ed"}}