> Markdown version of [/jobs/ext/4567055-java-ai-developer](https://www.wearedevelopers.com/jobs/ext/4567055-java-ai-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Java AI Developer

- **Company:** CYNET SYSTEMS INC.
- **Location:** Palo Alto, CA, United States
- **Salary:** $110,240.0 - $118,560.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Amazon S3, Software Applications, Computer Programming, DevOps, Amazon DynamoDB, Machine Learning, Cloud Services, Tensorflow, Pytorch, Large Language Models, Spring-boot, Generative AI, Backend, Cloudformation, Event Driven Architecture, Kubernetes, Functional Programming, Api Gateway, Restful APIs, Terraform, Docker, Jenkins, Microservices
- **Published:** November 4, 2026
- **Apply:** https://www.thejobnetwork.com/job/85f85d15-1ba6-4dae-9a35-2b49afb22e91/java-ai-developer

## About the Role

* Seeking a Java AI Developer with strong programming skills and experience in cloud services to design and implement AI-powered applications.

Requirement/Must Have:

 * Strong hands-on experience in Java (17+ preferred) and Spring Boot.
 * Proven experience with AWS services (Lambda, EMR, S3, RDS, EKS/ECS).
 * Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and experience with generative AI tools (e.g., Bedrock, SageMaker).
 * Experience with Terraform or CloudFormation.
 * Understanding of microservices, event-driven architectures, and RESTful API design.
 * Experience with Docker, Kubernetes, and Jenkins.

## Description

* Design, develop, and implement AI-powered automation and applications using AWS Bedrock, LLMs (Large Language Models), or SageMaker.
 * Develop robust backend services and RESTful APIs using Java 17/21, Spring Boot, and microservices architecture.
 * Build scalable, resilient solutions utilizing AWS services such as Lambda, S3, API Gateway, and DynamoDB.
 * Implement CI/CD pipelines to automate the deployment, monitoring, and operational lifecycle of AI models.
 * Process and clean data to feed machine learning models, creating intelligent algorithms to enhance automation.
 * Work with cross-functional teams (data scientists, DevOps) to translate business requirements into technical AI solutions.