Java Full Stack Developer

Role & responsibilities

We are seeking a highly skilled Senior Software Engineer with strong hands-on experience in Java/J2EE, Spring Boot, Microservices, Kafka, Cloud technologies, and modern AI/GenAI technologies. The ideal candidate will be responsible for designing and developing scalable, high-performance enterprise applications, building event-driven architectures, leveraging cloud platforms, and integrating AI capabilities into modern software solutions.

Key Responsibilities

• Design, develop, and maintain scalable full-stack applications using Java, Spring Boot, Microservices, and related technologies.
• Develop robust, secure, and high-performance backend services and RESTful APIs.
• Design and implement event-driven and distributed applications using Apache Kafka.
• Develop Kafka producers/consumers, event-driven workflows, message processing, and asynchronous integrations.
• Build responsive and reusable frontend components using ReactJS, Redux, and JavaScript.
• Design, develop, and deploy applications on cloud platforms such as AWS, Azure, or GCP.
• Design and implement AI-enabled applications and features using Generative AI, LLMs, APIs, and cloud-based AI services.
• Integrate LLM/GenAI capabilities into enterprise applications based on business requirements.
• Develop and consume REST APIs and integrate with third-party systems, platforms, AI services, and cloud services.
• Participate in architecture and technical design discussions and contribute to scalable, resilient, and highly available application design.
• Perform code reviews, debugging, performance tuning, and production issue resolution.
• Leverage AI-assisted development tools to improve coding, testing, debugging, documentation, and developer productivity.
• Collaborate with Product Owners, Architects, QA, DevOps, and other stakeholders to deliver high-quality solutions.
• Follow best practices for secure coding, application security, cloud security, data privacy, and responsible AI usage.
• Contribute to continuous improvement of development processes, engineering standards, and application architecture.

Must-Have Skills

• 5+ years of hands-on experience in Java/J2EE development.
• Strong expertise in Spring Boot, Spring MVC, Spring Security, and Spring Cloud.
• Proven experience developing Microservices-based architectures.
• Strong experience with Apache Kafka, including producers, consumers, topics, partitions, consumer groups, and event-driven architectures.
• Strong knowledge of REST APIs, JSON, web services, and third-party integrations.
• Hands-on experience with at least one major cloud platform AWS, Azure, or GCP.
• Good understanding of cloud-native application development, scalability, high availability, monitoring, and deployment.
• Good understanding of Design Patterns, OOP, SOLID principles, Clean Architecture, and scalable application design.
• Hands-on experience with Generative AI / AI application development concepts.
• Experience working with Large Language Models (LLMs) such as OpenAI, Azure OpenAI, Anthropic, Gemini, or equivalent platforms.
• Experience integrating LLM APIs / AI services into enterprise applications.
• Understanding of Prompt Engineering, prompt optimization, structured outputs, and LLM-based workflows.
• Good understanding of Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.
• Exposure to AI Agents / Agentic AI, tool/function calling, orchestration, and multi-step AI workflows.
• Experience with Git, CI/CD pipelines, Docker, and Kubernetes.
• Familiarity with Agile/Scrum methodologies.

AI / GenAI Skills

• Good understanding of Generative AI architecture and LLM application patterns.
• Experience integrating LLM APIs, AI SDKs, and cloud-based AI services.
• Understanding of RAG architecture, document ingestion, chunking, embeddings, vector search, and context management.
• Exposure to vector databases such as Pinecone, Azure AI Search, OpenSearch, Weaviate, Milvus, or equivalent.
• Understanding of AI Agents, function/tool calling, orchestration frameworks, and AI-powered workflows.
• Exposure to frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent is preferred.
• Knowledge of AI application security, including prompt injection, data leakage, access control, and responsible AI practices.
• Ability to identify suitable AI use cases and translate business requirements into scalable AI-enabled technical solutions.
• Experience implementing AI-powered features such as intelligent search, summarization, classification, conversational interfaces, recommendations, or developer productivity solutions is an advantage.

Cloud & DevOps Skills

• Hands-on experience with AWS, Azure, or GCP cloud platforms.
• Experience with cloud services such as compute, storage, databases, networking, IAM, monitoring, and messaging.
• Experience deploying and managing cloud-native microservices.
• Good understanding of Docker and Kubernetes.
• Experience with CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, Azure DevOps, or equivalent tools.
• Understanding of Infrastructure as Code (IaC) using Terraform, CloudFormation, or equivalent is preferred.
• Experience with cloud monitoring, logging, observability, and application performance management is an advantage.

Preferred candidate profile