Sr. Java Technical Lead with AI App Dev
Job Summary Experienced software engineer with 8-9 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. Key ResponsibilitiesDesign 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.Skill RequirementsStrong experience in developing and maintaining enterprise-grade applications using Java and/or Python.Hands-on experience in building AI and Generative AI applications for business use cases.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