Strong hands-on experience in Core Java (Java 8/11/17 or later)| object-oriented programming collections| concurrency| streams| and enterprise application development.
Strong experience with Spring Boot| REST APIs| microservices| and integration of AIcapabilities into Java-based enterprise applications.
Hands-on experience with Generative AI / Large Language Models (LLMs)| including promptengineering and secure consumption of enterprise AI services/APIs.
Experience building or integrating AI-powered developer/productivity tools| assistants| agents| or automation workflows into software engineering processes.
Understanding of Retrieval-Augmented Generation (RAG)| embeddings| semantic search| and vector databases.
Familiarity with AI agent/tool-calling patterns| orchestration frameworks| and Model Context Protocol (MCP) concepts Experience with databases such as PostgreSQL| MongoDB| Redis| or similar SQL/NoSQL technologies. Experience with Git| CI/CD pipelines| Docker/Kubernetes| and cloud platforms such as GCP|AWS| or Azure.
Understanding of enterprise security| authentication/authorization| data privacy| responsible AI| logging| monitoring| and production support practices.
Strong analytical| problem-solving| communication| and Agile/Scrum collaboration skills.
Roles & Responsibilities Design| develop| and enhance AI-enabled tools and capabilities using Java as the primary programming language.
Build Spring Boot microservices and REST APIs that securely integrate enterprise applications with LLMs and AI services.
Develop AI-assisted engineering workflows such as intelligent search| code/document analysis| summarization| knowledge assistance| and workflow automation.
Implement RAG-based solutions by integrating enterprise knowledge sources| embeddings| semantic retrieval| vector stores| and LLM-generated responses.
Build and integrate AI agent workflows with approved enterprise tools and APIs using.
