Senior Java Developer - GenAI & LLMs, Microservices

Smart IT Frame LLC

Irving (TX)

On-site

USD 130,000 - 180,000

Full time

2 days ago
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Job summary

Smart IT Frame LLC in Irving, TX, seeks an experienced Java Developer with Generative AI expertise to design, develop, and maintain scalable enterprise applications while integrating Generative AI, LLMs, and AI-powered solutions.

The role requires hands-on Java engineering with Spring Boot, REST APIs, microservices, and cloud technologies, and collaboration with engineering, data science, product, and DevOps teams to build intelligent applications using LLMs, RAG, and prompt engineering.

Qualifications

  • 8+ years of software development experience with Java.
  • Java 8/11/17/21 experience required.
  • Spring Boot, Spring Framework, and Spring Cloud experience.
  • REST APIs and Microservices development expertise.
  • OOP, design patterns, and SOLID principles knowledge.
  • Experience with Generative AI and LLMs.
  • Prompt engineering and RAG architecture experience.
  • LLM API integrations (OpenAI/Azure OpenAI, Gemini, Claude).
  • Embeddings, vector databases, AI agents familiarity.
  • Vector databases experience (Pinecone, Weaviate, Milvus, Chroma, or Azure AI Search).
  • SQL and NoSQL databases, Git, Maven/Gradle, Docker, CI/CD.

Skills

Java expertise
Spring Framework experience
REST APIs
Microservices
Generative AI & LLMs
Prompt Engineering
RAG architecture
CI/CD practices
Cloud technologies
OOP & design patterns
SQL/NoSQL

Tools

Java
Spring Boot
Spring Cloud
Docker
Git
Maven/Gradle

Job description

Smart IT Frame LLC in Irving, TX, seeks an experienced Java Developer with Generative AI expertise to design, develop, and maintain scalable enterprise applications while integrating Generative AI, LLMs, and AI-powered solutions.

The role requires hands-on Java engineering with Spring Boot, REST APIs, microservices, and cloud technologies, and collaboration with engineering, data science, product, and DevOps teams to build intelligent applications using LLMs, RAG, and prompt engineering.

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