Java AI Engineer
Job in
Phoenix, Maricopa County, Arizona, 85044, USA
Listed on 2026-06-02
Listing for:
AceStack
Full Time
position Listed on 2026-06-02
Job specializations:
-
Software Development
AI Engineer, Software Engineer, Cloud Engineer - Software, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Java AI Engineer
Location :
Phoenix, AZ (ONSITE)
FTE ONLY
Job Description
We are seeking a Senior Java Engineer to design and build AI-powered developer tools, Agentic workflows, and performance engineering frameworks. This role focuses on developing AI agents using Git Hub Copilot Agent Mode and Claude-based models within modern IDE environments such as Intelli
J to automate software engineering workflows across CI/CD pipelines, performance testing, and developer productivity tooling.
Must Have Technical/Functional Skills
Java, AI, Github Copilot Agent, Claude based models
Roles & Responsibilities
• Java Engineering
o Design and develop scalable Java tools and frameworks focusing on application Performance and Resiliency testing
o Build frameworks and reusable components to shift left and accelerate performance and resiliency testing.
o Build internal developer platforms and frameworks that accelerate engineering productivity.
o Develop services that interact with micro-services architectures and distributed systems.
• AI Agent Development
o Design and implement Agentic AI workflows that automate engineering tasks such as code analysis, PR validation, test orchestration, Results analysis and CI/CD operations.
o Build AI agents using Git Hub Copilot Agent Mode, leveraging Claude models and other LLMs.
o Develop developer productivity agents inside Intelli
J and Git Hub environments.
o Create AI-assisted tooling for root cause analysis, test generation, and system diagnostics.
• CI/CD Automation
o Build and optimize Git Hub Actions (GHA) pipelines for large-scale mono-repos and microservices architectures.
o Develop automation that integrates AI agents directly into CI/CD workflows.
o Implement automated checks for:
o performance regressions
o code quality
o test coverage
o release readiness
• Performance Engineering
o Design frameworks for performance testing automation and continuous performance validation.
o Build tooling that integrates performance tests into CI/CD pipelines.
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