Description

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 secure tool-calling/orchestration patterns. • Apply prompt engineering, structured outputs, validation, guardrails, access controls, audit logging, and human-review patterns for reliable AI solutions. • Collaborate with product owners, architects, security, platform, data, and engineering teams to translate use cases into scalable AI solutions. • Create automated unit, integration, and API tests and participate in code reviews to maintain engineering quality. • Support CI/CD, containerized deployment, observability, troubleshooting, performance tuning, and production readiness of AI-enabled services. • Evaluate new AI capabilities and frameworks through proofs of concept and recommend practical approaches aligned with enterprise standards." SKILLS_REQUIRED "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 AI capabilities into Java-based enterprise applications. • Hands-on experience with Generative AI / Large Language Models (LLMs), including prompt engineering 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" DESIRABLE_SKILLS "Strong communication, collaboration, ownership, technical curiosity, problem-solving, adaptability, and ability to work effectively with cross-functional engineering and product teams" KEYWORDS "Java, Core Java, Spring Boot, REST API, Microservices, Generative AI, GenAI, LLM, RAG, AI Agents, Agentic AI, Prompt Engineering, Semantic Search, Vector Database, Embeddings, MCP, Tool Calling, Python, PostgreSQL, MongoDB, Redis, Docker, Kubernetes, GCP, AWS, Azure, Git, CI/CD" EXPERIENCE_RANGE_IN_REQUIRED_SKILLS 6 - 8 Years
 

Key Skills

Education

Bachelor's degree