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# Java Backend Engineer

- **Company:** InfoVision, Inc.
- **Location:** Irving, TX, United States
- **Contract:** Contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, Databases, Hibernate (Java), Java Persistence API, Spring Framework, PostgreSQL, Routing, Role-Based Access Control, OpenAI, Cloud Services, Logstash, Prometheus, Enterprise Software Applications, Real Time Systems, Spring-mvc, Retrieval-Augmented Generation, Large Language Models, Spring-boot, Backend, Kotlin, LiteLLM, Model Context Protocol, GPT
- **Published:** October 30, 2026
- **Apply:** https://www.dice.com/job-detail/b3afec85-83a8-4d9f-b8c3-92e37708c401

## About the Role

* Extensive experience building enterprise applications with Java 17 and Kotlin.
 * Deep expertise in the Spring ecosystem, specifically Spring Boot 3.5+, Spring MVC, and reactive paradigms using Spring WebFlux.
 * Strong background in data modeling and database interaction using PostgreSQL, JPA, Hibernate Envers, and reactive drivers like R2DBC.
 * Proven track record of designing secure, multi-tenant backend architectures with tenant-level isolation.
 * Experience configuring and deploying cloud services, specifically AWS S3 for object storage and AWS Secrets Manager for runtime credential management.
 * Familiarity with modern observability and telemetry tools, including Prometheus, Micrometer, Logstash

## Description

* Platform Engineering: Design and implement highly scalable backend services using Java 17, Kotlin 1.9.25, and Spring Boot 3.5.11.
 * Reactive & Real-Time Systems: Develop non-blocking, real-time AI chat capabilities using Spring WebFlux, R2DBC, and Server-Sent Events (SSE) within the Shannon Agent Server.
 * Multi-Tenant Architecture: Architect dynamic database routing and auto-migrations across distinct PostgreSQL tenant databases using Flyway.
 * AI & LLM Integration: Build adapter-pattern interfaces to seamlessly route requests across multiple LLM providers, including Azure OpenAI, OpenAI (GPT API v4.9), and LiteLLM.
 * Extensibility & Tooling: Implement Model Context Protocol (MCP) servers and tools, alongside RAG and Vector Store capabilities, to extend the platform's AI reasoning.
 * Security & Identity: Secure APIs and SDK configurations implementing robust authentication flows, including JWT Bearer Tokens, HMAC request signing, and Role-Based Access Control (RBAC).
 * Data & State Management: Build multi-device sync, chat backup/restore, and secure file handling utilizing AWS S3 and pre-signed URLs within the Shannon Sync Server.