Sr Full stack Java Developer

Role overview

Core responsibilities

• Build AI-powered applications using Java, Spring Boot, front-end frameworks, REST APIs, and cloud-native technologies.
• Integrate generative AI and large language models into enterprise applications.
• Develop RAG solutions using enterprise documents, knowledge bases, vector databases, and semantic search.
• Implement prompt engineering, response validation, context management, and AI guardrails.
• Develop reusable React or Angular components using TypeScript, JavaScript, HTML5, and CSS3.
• Design scalable microservices using Spring Boot, Spring Cloud, and API Gateway.
• Develop REST and event-driven integrations with AI platforms, enterprise systems, databases, and external services.
• Apply application security practices including OAuth 2.0, JWT, RBAC, and API security.
• Containerize and deploy microservices with Docker, Kubernetes, and cloud platforms.
• Develop CI/CD pipelines and automated software tests.

Required experience

• At least five years of professional software development experience.
• Strong expertise in Java and Spring Boot.
• Full-stack development experience with REST APIs, React or Angular, JavaScript, and TypeScript.
• Experience designing scalable, microservices-based, cloud-native applications.
• Experience integrating generative AI, large language models, and AI APIs into enterprise applications.
• Strong understanding of RAG, embeddings, vector databases, semantic search, prompt engineering, and LLM orchestration.
• Experience with OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar platforms.
• Experience with RESTful APIs, JSON services, and third-party integrations.
• Strong database experience with PostgreSQL, MySQL, MongoDB, Redis, or similar technologies.
• Experience with Kafka, RabbitMQ, or other event-driven messaging platforms.
• Hands-on experience with Docker, Kubernetes, CI/CD, Jenkins, Maven, Git, and cloud deployment.
• Knowledge of Spring AI, LangChain/LangGraph, or comparable frameworks is highly desirable.

Technical capabilities

• Implement vector retrieval using Pinecone, Azure AI Search, Elasticsearch, or PostgreSQL with pgvector.
• Use Spring Security, OAuth 2.0, JWT, RBAC, and API security practices.
• Implement asynchronous processing with Kafka, RabbitMQ, or cloud messaging services.
• Use JUnit, Mockito, REST Assured, Selenium, Playwright, or Cypress for automated testing.
• Add logging, metrics, distributed tracing, health checks, and application monitoring.
• Optimize caching, database performance, APIs, asynchronous processing, and LLM utilization.