Java Full stack AI_MK

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.