Summary
✨ AI‑Generated
An enterprise technology team is seeking a Senior Java Backend Developer to build scalable microservices while integrating Generative AI and LLM capabilities. The role covers prompt orchestration, RAG services, AI inference, secure integrations, automated evaluation, observability, CI/CD, containerization, and cloud-native engineering.
Highlights
Senior backend role combining Java microservices with hands-on Generative AI and LLM integration, prompt engineering, RAG, secure APIs, scalability, observability, CI/CD, and cloud-native practices.
Description
Design, develop, and maintain highperformance backend services using Java (17+), Spring Boot, and Microservices architectureBuild and expose RESTful and eventdriven APIs supporting enterprisescale applicationsIntegrate Generative AI / LLM capabilities (e.g., text generation, summarization, Q&A, classification) into backend workflowsDesign, test, and optimize prompts and prompt orchestration strategies to ensure accuracy, determinism, and performanceDevelop AIaware backend components such as:Prompt templates and prompt pipelinesRetrievalAugmented Generation (RAG) servicesAI inference orchestration layersImplement secure API integrations with AI platforms and internal data sources, ensuring compliance with enterprise security standardsApply prompt versioning, evaluation, and monitoring techniques to improve AI output quality over timeEnsure nonfunctional requirements: scalability, resiliency, performance, and observabilityContribute to CI/CD pipelines, containerization, and cloudnative deploymentsParticipate in code reviews, architecture discussions, and technical design decisionsSupport production systems and troubleshoot complex backend or AIintegration issuesRequired Technical SkillsCore Backend Engineering5+ years of strong handson experience in Java backend developmentExpertise in Java 11/17+, Spring Boot, Spring MVC, Spring SecuritySolid experience in Microservices, REST APIs, and API design (OpenAPI/Swagger)Experience with containers and cloud platforms (Docker, Kubernetes, OpenShift, Azure/AWS)Strong knowledge of SQL and NoSQL databases (e.g., DB2, PostgreSQL, MongoDB)Experience in CI/CD, DevOps practices, and automated testingAI & Prompt EngineeringHandson experience integrating Large Language Models (LLMs) into backend systemsStrong understanding of prompt engineering techniques, including:Zeroshot, fewshot, and chainofthought promptingPrompt templates and dynamic prompt generationGuardrails, validation, and hallucination reductionExperience building RAGbased solutions using vector stores and embeddingsFamiliarity with AI orchestration frameworks or SDKs (enterprise or opensource)Ability to evaluate prompt and model responses for quality, bias, and consistencySecurity & ComplianceExperience implementing OAuth2.0, JWT, SSL/TLS, and secure API patternsAwareness of data privacy, PII handling, and AI governance in regulated environments (BFSI preferred)
