Java Full Stack Developer

Key Responsibilities

• Design, develop, and maintain backend services using Java, Spring Framework, Spring Boot, and Hibernate.

• Build and consume Microservices architectures with secure, scalable, and reliable communication.

• Develop responsive and user-friendly React-based frontend interfaces.

• Implement server-side components and APIs using Node.js where required.

• Integrate applications with cloud platforms (AWS/Azure/GCP) for deployment, storage, and scalability.

• Collaborate closely with cross-functional teams (Product, QA, DevOps, UI/UX).

• Participate in code reviews, performance optimization, troubleshooting, and debugging.

• Maintain coding standards, documentation, and ensure secure coding practices.

• Support CI/CD pipelines, containerization, and DevOps activities for smooth deployments.

• Agentic AI Development

• Build and integrate AI agents using frameworks such as:

  • LangChain / LangGraph

  • OpenAI Assistants / ReAct / AutoGen

  • HuggingFace, LlamaIndex, or custom agentic frameworks

• Develop advanced agentic workflows including:

  • Tool calling and function calling

  • Task planning and retrieval-augmented generation (RAG)

  • Dynamic reasoning and multi-agent collaboration

• Integrate leading LLMs (GPT, Claude, Llama, Mistral, etc.) into Java-based systems.

• Build workflows and pipelines for prompt engineering, model orchestration, and inference.

Required Skills & Qualifications

• 4–7 years of hands-on experience in full stack development.

• Strong backend development experience with:

  • Java, Spring, Spring Boot

  • Hibernate/JPA

  • RESTful APIs

  • Microservices architecture

• Frontend development experience using React, JavaScript, TypeScript, HTML5, CSS3.

• Experience with Node.js for backend or middleware services.

• Knowledge of Cloud technologies (AWS, Azure, or GCP)—deployments, storage, compute, container services, etc.

• Strong communication and collaboration skills.

• Ability to work independently and take end-to-end ownership.

• Basic understanding of AI/ML, such as:

  • Integrating machine learning models

  • Using cloud AI services (Vision, NLP, Recommendations)

  • Working with AI APIs/SDKs

• Familiarity with:

  • Git, Maven/Gradle

  • CI/CD tools (Jenkins, GitHub Actions, GitLab CI, etc.)

  • Docker/Kubernetes basics

  • SQL/NoSQL databases (MySQL, PostgreSQL,

  • MongoDB)

Preferred Qualifications

• Experience working in Agile/Scrum environments.

• Exposure to messaging systems like Kafka or RabbitMQ.

• Knowledge of security standards (OAuth2, JWT, SSL).

• Experience with monitoring tools (Prometheus, ELK, Grafana).