Java Backend Developer with AI/DLC

Job Title: Java Backend Developer with AI/DLC

Location: Austin, TX or Southlake, TX.

Duration: 6 to 12 Months
Employment Type: Contract-to-Hire

Experience: 10+ Years

Job Overview

We are looking for an experienced Java Backend Developer with AI/DLC experience to design, develop, and maintain scalable backend applications and microservices.

The ideal candidate will be a strong Java/Spring Boot backend engineer first, with hands-on experience using modern AI tools and Generative AI capabilities to improve software development, application modernization, coding productivity, testing, debugging, and solution design.

The candidate should have strong experience with Java, Spring Boot, REST APIs, Microservices, Kafka, distributed systems, databases, and cloud technologies, along with practical exposure to AI-assisted development and GenAI technologies.

Key Responsibilities:

Java Backend Development

• Design, develop, and maintain scalable backend applications using Java and Spring Boot.
• Build and maintain RESTful APIs and microservices.
• Develop highly available and fault-tolerant backend services.
• Apply object-oriented programming, design patterns, and clean coding practices.
• Develop reusable and maintainable backend components.
• Participate in application modernization and migration initiatives.

Microservices & Distributed Systems

• Design and develop distributed microservices architectures.
• Work with Kafka and event-driven architectures.
• Implement asynchronous processing, messaging, retries, error handling, and resiliency patterns.
• Troubleshoot performance and scalability issues across distributed systems.
• Participate in backend system design and architecture discussions.

AI / DLC / AI-Assisted Development

The candidate should be comfortable using AI-assisted development tools as part of the software engineering lifecycle.

Experience with tools such as:

• GitHub Copilot
• Claude / Claude Code
• Cursor
• ChatGPT
• Gemini
• Other enterprise AI coding assistants

Use AI capabilities for:

• Code generation and refactoring
• Debugging and troubleshooting
• Unit-test generation
• Code reviews
• Documentation
• Legacy code modernization
• Developer productivity
• Application migration and transformation
• API and microservice development

Generative AI Exposure

Experience with one or more of the following is preferred:

• Generative AI / LLMs
• Prompt engineering
• RAG – Retrieval-Augmented Generation
• Embeddings
• Vector databases
• LLM APIs
• AI-powered applications
• AI agents / Agentic AI
• LangChain / LangGraph
• MCP / Model Context Protocol

The candidate does not need to be a pure AI/ML engineer. Strong backend engineering experience combined with practical AI exposure is the primary requirement.

Cloud & DevOps

Experience with one or more cloud platforms:

• AWS
• Azure
• Google Cloud Platform (Google Cloud Platform)

Preferred experience:

• Docker
• Kubernetes
• Jenkins
• GitHub Actions
• GitLab CI/CD
• CI/CD pipelines
• Infrastructure/application deployment
• Cloud-native application development

Database & Messaging

Experience with:

• SQL databases
• PostgreSQL / MySQL / Oracle / SQL Server
• NoSQL databases
• Kafka
• Event-driven architecture
• Redis or similar caching technologies

Required Technical Skills

Must Have:

• Java 8/11/17/21
• Spring Boot
• Spring Framework
• REST APIs
• Microservices
• Kafka
• Distributed systems
• Object-Oriented Programming
• SQL
• Git
• Unit testing
• Strong backend system design

Strongly Preferred:

• AWS / Azure / Google Cloud Platform
• Docker / Kubernetes
• CI/CD
• Event-driven architecture
• NoSQL
• Performance optimization

AI/DLC Experience:

• GitHub Copilot
• Claude Code
• Cursor
• ChatGPT
• Gemini
• Generative AI / LLMs
• RAG
• AI-assisted coding
• AI-powered application development

Nice to Have:

• LangChain
• LangGraph
• MCP
• Agentic AI
• Vector databases
• Embeddings
• LLM evaluation
• AWS Bedrock / Azure OpenAI / Vertex AI