Java Full Stack Developer
Job Title: Java Full Stack Developer – AI & AWS
Location: Plano, TX
Experience: Mid-Senior LevelJob Summary
We are seeking an experienced Java Full Stack Developer with expertise in AI integration and AWS cloud technologies to transform prototypes developed using AI-assisted coding tools into secure, scalable, production-ready enterprise applications. The ideal candidate will have strong Java development skills, full-stack engineering experience, cloud deployment expertise, and a solid understanding of Generative AI, LLMs, and enterprise security standards.
Key Responsibilities:
Design, develop, test, and deploy enterprise applications using Java and modern front-end technologies.
Transform prototypes and proof of concepts built with GitHub Copilot, Kiro, or similar tools into production-ready applications.
Integrate AWS services, including Amazon S3, AWS Lambda, and Amazon Bedrock, into application architectures.
Develop and maintain REST APIs, microservices, and scalable backend services.
Implement CI/CD pipelines, infrastructure as code, and automated deployment workflows.
Use Docker and Kubernetes for application containerization and orchestration.
Integrate Generative AI capabilities, including LLMs, RAG, embeddings, vector databases, and AI agents.
Implement enterprise authentication, authorization, data protection, and security controls.
Develop automated unit, integration, and UI tests to ensure application reliability.
Implement monitoring, logging, alerting, and incident response processes for production applications.
Collaborate with architecture, DevOps, security, and product teams to ensure enterprise compliance.
Maintain technical documentation, operational runbooks, and production support procedures.
Required Qualifications:
Strong experience in Java, Spring Boot, and full-stack application development.
Proficiency in front-end technologies such as JavaScript, TypeScript, React, or Angular.
Hands-on experience with AWS services, particularly S3, Lambda, and Bedrock.
Experience converting prototypes into secure, scalable enterprise applications.
Knowledge of REST APIs, microservices, Docker, Kubernetes, and Terraform.
Experience with CI/CD pipelines, Git, code reviews, and automated testing.
Strong understanding of enterprise security, IAM, authentication, and authorization.
Proficiency with AI-assisted development tools such as GitHub Copilot, Claude Code, or Kiro.
Knowledge of Generative AI concepts, including prompt engineering, RAG, agentic AI, embeddings, vector databases, and AI evaluation.
Familiarity with production monitoring, troubleshooting, and operational support.
Preferred Qualifications:
Experience with Model Context Protocol (MCP), reasoning models, graph databases, and LLM integration.
Knowledge of MLOps, model evaluation, AI guardrails, and fine-tuning techniques.
Experience with observability tools and cloud infrastructure automation.
Background in regulated industries or large enterprise environments.
Strong problem-solving, communication, and technical documentation skills.