Java with React JS

Location: Bengaluru, India

Experience: 5–8 years

Employment Type: Full-time / Permanent

We are looking for an experienced Full Stack Developer with strong proficiency in Java (backend), React.js (frontend), and hands-on exposure to AI/ML integration. The ideal candidate will design, develop, and deploy intelligent web applications that combine modern full-stack technologies with AI-driven features.

• Design, develop, and maintain scalable backend services using Java (Spring Boot).
• Build responsive and dynamic frontend applications using React.js, TypeScript, HTML5, and CSS3.
• Integrate AI/ML models and APIs (custom or third-party like OpenAI, Hugging Face, or AWS AI services) into applications.
• Collaborate with data scientists and AI engineers to integrate machine learning pipelines into production systems.
• Implement RESTful APIs and microservices architectures for efficient client–server communication.
• Ensure the application’s performance, responsiveness, and security.
• Deploy and manage solutions in cloud environments (AWS, Azure, or GCP).
• Participate in Agile development processes including sprint planning, code reviews, and retrospectives.
• Continuously explore new technologies, especially in AI/ML, LLMs, and frontend frameworks, to improve product capabilities.

• 5+ years of full-stack software development experience.
• Strong hands-on experience with Java 8+, Spring Boot, and REST API development.
• Proficiency in React.js, TypeScript, HTML5, and CSS3.
• Good understanding of state management (Redux, Context API) and frontend performance optimization.
• Experience working with AI/ML libraries, APIs, or SDKs (e.g., TensorFlow, PyTorch, OpenAI API, or similar).
• Familiarity with cloud-based AI services (AWS SageMaker, Azure Cognitive Services, GCP Vertex AI).
• Experience with Git, CI/CD pipelines, and containerization (Docker, Kubernetes).
• Solid understanding of RDBMS/NoSQL databases (MySQL, PostgreSQL, MongoDB).
• Excellent problem-solving, analytical, and communication skills.

• Exposure to Large Language Models (LLMs) and RAG (Retrieval-Augmented Generation) pipelines.
• Experience integrating AI assistants, chatbots, or recommendation systems into web apps.
• Familiarity with GraphQL, WebSockets, or micro-frontend architectures.
• Understanding of DevOps and MLOps workflows.
• Knowledge of prompt engineering or AI model fine-tuning.