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# Senior Java Developer with Agentic AI

- **Company:** Agentic AI LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $166,400.0 - $187,200.0
- **Contract:** Contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Automation of Tests, Software Code Optimization, Software Quality, Code Review, Continuous Integration, Software Debugging, NoSQL, Systems Development Life Cycle, Software Tools, Secure Coding, Software Engineering, Agentic-AI, Kubernetes, Production Code, Apache Kafka, Video Streaming, Splunk, Code Restructuring, Dynatrace
- **Published:** October 16, 2026
- **Apply:** https://www.dice.com/job-detail/76e1be8f-9c34-44b8-957d-2820fae1a38b

## About the Role

* Must have 10+ years of experience.
 * Must be willing to work on W2 only.
 * Must be willing to relocate to New York City, NY, if required.

Client Mandatory Skills: Java, Agentic AI, AI-assisted coding, code optimization, Kubernetes, streaming technologies/Kafka, NoSQL, CI/CD, automated testing, secure coding, code reviews, alerts and monitoring, Splunk/Dynatrace.

Preferred Skill: AWS

## Description

We are seeking an experienced Senior Java Developer with expertise in modern application development and AI-assisted engineering practices. The ideal candidate will have strong Java development skills and hands-on experience using AI tools to optimize code, accelerate development, and improve software quality., * Develop, review, debug, and maintain secure, high-quality production code.

 * Leverage approved AI-assisted engineering tools for code optimization, refactoring, debugging, and development acceleration.
 * Apply AI-assisted code reviews, test generation, release readiness checks, and incident/root-cause analysis.
 * Establish and follow standards for secure coding, peer reviews, and automated testing.
 * Use SDLC tools, CI/CD pipelines, and automation to improve software delivery.
 * Contribute to application design, functionality, scalability, and technical operations.
 * Support cloud-native applications using Kubernetes and AWS technologies.
 * Implement monitoring, alerting, and troubleshooting practices to improve application reliability.
 * Promote reusable engineering patterns, development standards, and best practices across teams.