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Java AI Engineer

Job in Phoenix, Maricopa County, Arizona, 85001, USA
Listing for: Ace Stack
Full Time position
Listed on 2026-07-01
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), AI QA / Validation Engineer, Backend Developer, AI Reliability/ Performance Engineer
Job Description & How to Apply Below

Java AI Engineer

Location:

Phoenix, AZ (ONSITE) FTE ONLY

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 IntelliJ 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

  • Design and develop scalable Java tools and frameworks focusing on application Performance and Resiliency testing
  • Build frameworks and reusable components to shift left and accelerate performance and resiliency testing.
  • Build internal developer platforms and frameworks that accelerate engineering productivity.
  • Develop services that interact with micro-services architectures and distributed systems.

· AI Agent Development

  • Design and implement Agentic AI workflows that automate engineering tasks such as code analysis, PR validation, test orchestration, Results analysis and CI/CD operations.
  • Build AI agents using Git Hub Copilot Agent Mode, leveraging Claude models and other LLMs.
  • Develop developer productivity agents inside IntelliJ and Git Hub environments.
  • Create AI-assisted tooling for root cause analysis, test generation, and system diagnostics.

· CI/CD Automation

  • Build and optimize Git Hub Actions (GHA) pipelines for large-scale mono-repos and microservices architectures.
  • Develop automation that integrates AI agents directly into CI/CD workflows.
  • Implement automated checks for:
    • performance regressions
    • code quality
    • test coverage
    • release readiness

• Performance Engineering

  • Design frameworks for performance testing automation and continuous performance validation.
  • Build tooling that integrates performance tests into CI/CD pipelines.
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