AI Integration Engineer

About the role

Experienced software engineer with 5-6 years of expertise in Java-based enterprise application development and 1-2 years of hands-on experience in AI and Generative AI application development. Skilled in designing, developing, and deploying AI-powered solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agent-based frameworks, and document processing technologies. Strong background in building scalable microservices-based applications using Java/Python, Spring AI, MongoDB, and cloud-native architectures.

Requirements

• 5 – 6 years Development experience in Java applications
• 1 year strong experience in AI app development

Skills

• Google ADK
• Google Doc AI
• Lang Graph
• Lang Chain
• RAG Java/Python
• Spring AI
• Mongo
• Hibernate
• Microservices
• Proficiency in developing AI agents using Google Agent Development Kit (ADK)
• Experience with Google Document AI for intelligent document processing and data extraction
• Strong knowledge of LangChain for developing LLM-powered workflows and applications
• Experience using LangGraph to design and orchestrate multi-agent and agentic AI solutions
• Expertise in implementing Retrieval-Augmented Generation (RAG) architectures and knowledge retrieval pipelines
• Experience integrating Large Language Models (LLMs) into enterprise applications
• Strong knowledge of Spring AI and Spring Boot for AI-enabled application development
• Hands-on experience in designing and developing Microservices-based architectures
• Proficiency in MongoDB for data storage and retrieval
• Experience with Hibernate/JPA for database persistence and ORM implementation
• Strong understanding of RESTful API design, development, and integration
• Experience in application performance optimization, debugging, and troubleshooting
• Knowledge of software development best practices, including testing, code reviews, and CI/CD processes
• Ability to collaborate with cross-functional teams and translate business requirements into technical solutions
• Strong problem-solving, analytical, and communication skills

Responsibilities

• Design and develop AI-powered applications using LLMs, RAG, and agentic frameworks.
• Build and integrate AI agents using Google ADK, LangGraph, and LangChain.
• Develop intelligent document processing solutions using Google Document AI.
• Implement Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge management.
• Design and develop RESTful microservices using Java, Spring Boot, and Spring AI.
• Integrate AI services with enterprise applications and backend systems.
• Design databases and data models using MongoDB and Hibernate/JPA.
• Optimize AI application performance, scalability, and reliability.
• Work closely with business stakeholders to identify AI use cases and translate requirements into solutions.
• Perform code reviews, testing, deployment, and production support.
• Ensure adherence to software engineering best practices, security standards, and AI governance guidelines.
• Mentor junior developers and contribute to AI solution architecture.