Sr Java Backend Developer

Original job posting

Design and maintain high-performance Java backend services and microservices architecture. Integrate Generative AI and LLM capabilities into backend workflows using RAG and prompt orchestration.

Job details

Design, develop, and maintain highperformance backend services using Java (17+), Spring Boot, and Microservices architecture Build and expose RESTful and eventdriven APIs supporting enterprisescale applications Integrate Generative AI / LLM capabilities (e.g., text generation, summarization, Q&A, classification) into backend workflows Design, test, and optimize prompts and prompt orchestration strategies to ensure accuracy, determinism, and performance Develop AIaware backend components such as: Prompt templates and prompt pipelines RetrievalAugmented Generation (RAG) services AI inference orchestration layers Implement secure API integrations with AI platforms and internal data sources, ensuring compliance with enterprise security standards Apply prompt versioning, evaluation, and monitoring techniques to improve AI output quality over time Ensure nonfunctional requirements: scalability, resiliency, performance, and observability Contribute to CI/CD pipelines, containerization, and cloudnative deployments Participate in code reviews, architecture discussions, and technical design decisions Support production systems and troubleshoot complex backend or AIintegration issues Required Technical Skills Core Backend Engineering 5+ years of strong handson experience in Java backend development Expertise in Java 11/17+, Spring Boot, Spring MVC, Spring Security Solid 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 testing AI & Prompt Engineering Handson experience integrating Large Language Models (LLMs) into backend systems Strong understanding of prompt engineering techniques, including: Zeroshot, fewshot, and chainofthought prompting Prompt templates and dynamic prompt generation Guardrails, validation, and hallucination reduction Experience building RAGbased solutions using vector stores and embeddings Familiarity with AI orchestration frameworks or SDKs (enterprise or opensource) Ability to evaluate prompt and model responses for quality, bias, and consistency Security & Compliance Experience implementing OAuth2.0, JWT, SSL/TLS, and secure API patterns Awareness of data privacy, PII handling, and AI governance in regulated environments (BFSI preferred)

What you’ll do

Design and maintain high-performance Java backend services and microservices architecture. Integrate Generative AI and LLM capabilities into backend workflows using RAG and prompt orchestration.

Requirements

Requires over 5 years of experience in Java backend development with expertise in Spring Boot and cloud platforms. Must have hands-on experience integrating LLMs and applying prompt engineering techniques.

Listed skills

• Microsoft Azure · Preferred
• Kubernetes · Preferred
• SQL · Preferred
• REST APIs · Preferred
• CI/CD · Preferred
• Docker · Preferred
• Amazon Web Services · Preferred
• prompt engineering · Preferred
• Spring Boot · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Java 17
• Spring Boot
• Microservices
• REST APIs
• Generative AI
• LLM Integration
• Prompt Engineering
• RAG
• Docker
• Kubernetes
• SQL
• NoSQL
• CI/CD
• OAuth2.0
• Azure
• AWS

Job areas

• Software
• Technology
• Engineering
• Consulting