Java Full stack AI_MK

Job description

**Role & responsibilities** We are looking for passionate **Full Stack Engineers with AI Engineering expertise** to join our emerging AI and Automation practice. The ideal candidate will have strong experience in **Java-based backend development, Angular frontend development**, and a keen interest in building and integrating **AI-powered applications, agentic workflows, and multi-agent systems** to solve complex business problems. This role offers an opportunity to work on next-generation AI solutions, integrating Large Language Models (LLMs), AI orchestration frameworks, and enterprise applications in a fast-paced, innovation-driven environment. **Preferred candidate profile** - Design, develop, and maintain scalable full-stack applications using **Java, Spring Boot, Angular, and REST APIs**. - Build and integrate **AI-powered solutions**, including agent-based workflows and multi-agent systems. - Develop and optimize backend services, APIs, and microservices architectures. - Collaborate with AI engineers and business stakeholders to translate requirements into intelligent solutions. - Integrate LLM-based applications using frameworks such as LangChain, LangGraph, OpenAI, Azure OpenAI, or similar platforms. - Implement prompt engineering, RAG (Retrieval-Augmented Generation), and workflow orchestration patterns. - Ensure application performance, security, scalability, and maintainability. - Participate in architecture design, code reviews, testing, and deployment activities. - Work in Agile teams and contribute to continuous improvement initiatives. **Full Stack Development** - Strong experience in **Java 8/11/17**, Spring Boot, Microservices. - Hands-on experience with **Angular (preferred Angular 10+)**. - Expertise in RESTful APIs and backend integrations. - Knowledge of SQL/NoSQL databases. - Experience with Git, CI/CD pipelines, and DevOps practices. - Familiarity with cloud platforms (Azure/AWS/GCP). **AI Engineering** - Understanding of Generative AI concepts and LLM applications. - Experience building or integrating AI workflows, chatbots, copilots, or intelligent assistants. - Exposure to **LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, OpenAI/Azure OpenAI**, or similar frameworks. - Knowledge of RAG, vector databases, embeddings, and prompt engineering. - Experience with Python for AI integrations is an added advantage.