Java & Gen AI Developer

Xaxis Solutions; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Xaxis Solutions in Dallas is actively seeking a skilled Java & GenAI Developer to design, develop, and integrate scalable Java applications with Generative AI capabilities. You will work on backend systems, REST APIs, microservices, and modern cloud technologies.

You will integrate LLMs, RAG, and prompt engineering into enterprise workflows, ensure secure authentication and API security, and collaborate with architects and data teams to deliver AI-powered solutions.

Qualifications

• Experience building GenAI-backed enterprise applications.
• Strong knowledge of Java, Spring Boot architecture.
• Experience with secure API design and data handling.

Responsibilities

• Develop and maintain scalable backend using Java and Spring Boot.
• Design RESTful APIs and microservices for enterprise apps.
• Integrate Generative AI/LLM capabilities into Java apps and workflows.
• Implement RAG solutions using vector stores and enterprise data sources.
• Apply prompt engineering, LLM integration, and AI-powered automation.
• Ensure authentication, authorization, and API security.

Skills

Java

Spring Boot

REST APIs

Microservices

Cloud

GenAI

LLM integration

Prompt engineering

OpenAI

Azure OpenAI

Tools

OpenAI

Azure OpenAI

Vector databases

Job description

We are looking for an experienced Java & GenAI Developer to design, develop, and integrate scalable Java-based applications with Generative AI capabilities. The ideal candidate should have strong expertise in Java, Spring Boot, REST APIs, microservices, and cloud technologies, along with hands-on experience integrating LLMs, RAG, prompt engineering, and AI services into enterprise applications.

Key Responsibilities

• Develop and maintain scalable backend applications using Java and Spring Boot.
• Design and implement RESTful APIs and microservices for enterprise applications.
• Integrate Generative AI/LLM capabilities into Java applications and business workflows.
• Develop RAG (Retrieval-Augmented Generation) solutions using enterprise data sources and vector databases.
• Implement prompt engineering, LLM integration, context management, and AI-powered automation.
• Integrate AI services and models through APIs/SDKs such as OpenAI, Azure OpenAI, or other LLM platforms.
• Develop and optimize AI-powered applications for performance, scalability, reliability, and security.
• Work with databases, vector stores, and search technologies to support GenAI applications.
• Implement secure authentication, authorization, API security, and responsible AI practices.
• Collaborate with architects, product teams, data engineers, and other developers to deliver AI-enabled enterprise solutions.
• Participate in code reviews, technical design discussions, testing, and production support.