Java Full Stack Feveloper

Project Description:

We are seeking a highly skilled Full Stack AI Engineer to design, develop, and maintain AI-enabled applications and intelligent agents that drive business automation and enhance user experiences. The role involves building scalable Java-based backend services, modern frontend applications, AI/GenAI capabilities using Python, and robust CI/CD pipelines. The candidate will work within a pod-based agile delivery model and take ownership of end-to-end solution delivery, quality, and operational readiness.

Responsibilities:

• Design, develop, and maintain AI-enabled applications, intelligent agents, and enterprise solutions.
• Develop scalable Java-based backend services, APIs, and microservices.
• Build responsive and intuitive frontend applications and user experiences.
• Implement AI, Machine Learning, and Generative AI capabilities using Python and related frameworks.
• Integrate Large Language Models (LLMs), AI agents, and conversational AI solutions into business applications.
• Develop and execute automated testing strategies and promote shift-left quality practices.
• Build, manage, and optimize CI/CD pipelines to support automated deployments.
• Produce technical documentation, architecture artifacts, and knowledge-sharing materials.
• Support production deployments, operational readiness, and post-deployment activities.
• Collaborate within a pod-based delivery model, taking accountability for delivery outcomes and business value.
• Troubleshoot application issues and drive continuous improvement initiatives.

Mandatory Skills Description:

• 7+ years of experience in Full Stack Application Development.
• Strong experience in Java, Spring Boot, REST APIs, and Microservices architecture.
• Proven expertise in Python development for AI/ML and Generative AI solutions.
• Experience building AI-enabled applications, chatbots, AI agents, or LLM-based solutions.
• Strong frontend development experience using React, Angular, JavaScript, or TypeScript.
• Experience with CI/CD tools such as Jenkins, GitHub Actions, Azure DevOps, or similar platforms.
• Strong understanding of automated testing frameworks and quality engineering practices.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Excellent problem-solving, collaboration, and communication skills.
• Experience working in Agile/Scrum or pod-based delivery environments.

Generative AI & LLMs:

• OpenAI / Azure OpenAI APIs

Prompt Engineering

RAG (Retrieval Augmented Generation)

LangChain / LangGraph

AI Agents

• Vector Databases (FAISS, ChromaDB, Pinecone anyone they can learn and come)
• FastAPI-based AI services

LLM Evaluation and Testing

Nice-to-Have Skills Description:

• React, Azure, AWS, Power BI, automation tools such as PowerApps, Power Automate.