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# Java Back-End Engineer (AI Technologies)

- **Company:** Nexiva Inc
- **Location:** O'Fallon, MO, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Automation of Tests, Microsoft Azure, Business Software, Cloud Computing, Distributed Systems, Spring Framework, NoSQL, Performance Tuning, Software Engineering, SQL Databases, Web Services, Data Logging, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Spring-boot, Generative AI, Backend, Event Driven Architecture, Virtual Agents, Api Gateway, Restful APIs, Docker, Microservices
- **Published:** July 26, 2026
- **Apply:** https://www.careerjet.com/jobad/us6b3f5abb8c78c10f4e0271ca930569e5

## About the Role

We are seeking a highly skilled Senior Java Back-End Engineer with strong AI expertise to design, develop, and deploy scalable backend systems and Agentic AI solutions. The ideal candidate will have extensive experience in Java/Spring Boot development, microservices, APIs, cloud platforms, and hands-on experience building AI-powered applications, LLM integrations, and autonomous AI agents., 7+ years of experience in software engineering and backend development.
Excellent experience with Spring Boot, Spring Framework, Spring AI, and Microservices.
Strong knowledge of REST APIs, Web Services, API Gateway, and distributed systems.
Strong experience with SQL and NoSQL databases.
Experience with Docker and Kubernetes.
AI / Agentic AI
Hands-on experience building Generative AI and Agentic AI applications.
Experience integrating LLMs and Foundation Models into production applications.
Understanding of AI agents, tool/function calling, multi-agent systems, agent memory, planning, and orchestration.

## Description

Design and develop scalable, secure, and high-performance backend services using Java, Spring Boot, and Microservices.
Build and integrate Agentic AI applications powered by Large Language Models (LLMs).
Develop AI agents capable of reasoning, planning, decision-making, tool calling, and executing multi-step tasks.
Develop RESTful APIs and event-driven architectures to support AI and business applications.
Build RAG (Retrieval-Augmented Generation) solutions using vector databases and enterprise data sources.
Implement AI agent orchestration, memory, context management, and workflow automation.
Work with frameworks and technologies such as LangChain, LangGraph, Spring AI, or similar AI agent frameworks.
Develop automated testing, monitoring, logging, and performance optimization strategies.
Deploy and manage applications on cloud platforms such as AWS, Azure, or GCP.


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