Experience: 5+ years, Java, AI, performance testing
Job Description & Details
"The intersection of Java development and AI-driven automation is reshaping how software teams deliver value, making expertise in this niche highly sought after. Companies are investing heavily in AI agents that can streamline CI/CD pipelines, performance testing, and developer productivity. This Java AI Engineer role offers a unique chance to build cutting\u2011edge tools that empower engineers while working on\u2011site in Phoenix.\n\n# Job Summary\nWe are looking for a Senior Java Engineer who will design and build AI\u2011powered developer tools, agentic workflows, and performance\u2011engineering frameworks. The role focuses on creating Java\u2011based platforms that accelerate performance and resiliency testing, integrate with micro\u2011service architectures, and embed AI agents (GitHub Copilot, Claude models) directly into IDEs like IntelliJ to automate code analysis, PR validation, and CI/CD operations.\n\n# Top 3 Critical Skills Table\n| Skill | Why it's critical | Mastery Level |\n|---|---|---|\n| Java (core & performance) | Foundation for building scalable tools and micro\u2011service integrations | Senior |\n| AI Agent Development (LLMs, Copilot) | Enables automation of code analysis, PR validation, and CI/CD tasks | Senior |\n| Performance & Resiliency Engineering | Guarantees tools handle load, detect bottlenecks, and improve reliability | Senior |\n\n# Interview Preparation\n1. **How would you design a Java framework that can shift\u2011left performance testing for micro\u2011services?**\n *What the interviewer is looking for:* Understanding of performance metrics, load testing tools, and how to embed testing hooks in Java services.\n2. **Explain how you would integrate GitHub Copilot Agent Mode with an IntelliJ plugin to automate PR validation.**\n *What the interviewer is looking for:* Knowledge of IntelliJ SDK, Copilot APIs, and workflow orchestration.\n3. **Describe the steps to build an AI agent using Claude models that generates test cases from code changes.**\n *What the interviewer is looking for:* Experience with LLM prompting, data extraction from diffs, and test generation pipelines.\n4. **What strategies would you use to ensure resiliency testing does not impact production environments?**\n *What the interviewer is looking for:* Isolation techniques, canary releases, and fault\u2011injection methods.\n5. **How do Kubernetes and Docker fit into the development of AI\u2011assisted tooling?**\n *What the interviewer is looking for:* Containerization benefits, orchestration for scaling AI services, and CI/CD integration.\n\n# Resume Optimization\n- Java\n- AI Agent Development\n- GitHub Copilot\n- Claude LLM\n- IntelliJ Plugin Development\n- Performance Testing\n- Resiliency Engineering\n- Kubernetes\n- Docker\n- Microservices Architecture\n\n# Application Strategy\nWhen reaching out to the recruiter, send a concise email that starts with a friendly greeting, attaches your updated resume, and clearly highlights your top relevant skills. Make sure to mention related skills you possess, such as Java performance engineering, AI agent development with LLMs, and experience building IntelliJ plugins. Reference specific projects where you automated CI/CD or built performance testing frameworks, and tie those achievements directly to the responsibilities listed in the job description.\n\n# Career Roadmap\n| Current Role | Typical Experience | Core Focus | Next Position |\n|---|---|---|---|\n| Java AI Engineer | 5\u20117 years Java, AI, performance | Build AI\u2011driven tooling & frameworks | Senior AI Engineer |\n| Senior AI Engineer | 7\u201110 years, lead projects, mentor | Architect enterprise\u2011scale AI platforms | Lead AI Engineer |\n| Lead AI Engineer | 10+ years, cross\u2011team ownership | Drive AI strategy, manage multiple squads | Director of AI Engineering |\n"