Application Engineer - AI-Driven Quality Engineering

Applications Developer 2

The Fusion Projects team is seeking an Application Engineer to drive quality and stability across Fusion applications. This role is responsible for executing large-scale certification cycles, developing and maintaining scalable frameworks, and validating integration touchpoints across dependent modules. As the organization accelerates AI-driven quality engineering within PPM and the broader ERP landscape, the ideal candidate will bring an AI-first mindset to modernize engineering practices, analytics, and continuous quality processes. The Application Engineer will leverage advanced technologies—such as generative capabilities, intelligent test design, defect prediction, and data-driven quality insights—to increase throughput, reduce cycle time, and improve release quality. This position is critical to supporting product delivery, customer success, and Oracle’s unified ERP  model by executing on the company’s AI roadmap.

ResponsibilitiesKey Responsibilities

• Lead and participate in end-to-end testing activities across ERP modules and integrated systems.
• Design, develop, and maintain comprehensive regression test suites for applications, platforms, and interfaces.
• Communicate test results, defects, and product quality insights clearly and effectively to stakeholders across teams.
• Provide expert-level support to business, development, and QA teams for both internal and customer-facing issues.
• Perform root cause analysis for defects and collaborate with engineering teams to ensure timely and high-quality fixes.
• Build automation solutions from the ground up and optimize existing frameworks for scalability, maintainability, and reusability.
• Solve complex automation challenges across diverse technologies, ensuring robust and efficient test solutions.
• Continuously enhance automation effectiveness by adopting innovative tools, advanced testing techniques, and modern architectural patterns.

Agile Methodology

• Experience of working in Agile environments using Scrum frameworks

Domain Knowledge

• Possess a foundational understanding of ERP concepts, business processes, and industry best practices.

AI in Quality Engineering 

• Apply AI/ML techniques to enhance QA processes—such as intelligent test case generation, test prioritization, root cause prediction, and failure pattern analysis.
• Utilize AI-driven tools for code analysis, defect clustering, and improving automation stability.
• Ability to work with AI-assisted development and testing tools (e.g., AI pair-testers, code analyzers, generative AI tools) to increase velocity and reduce manual effort.
• Strong conceptual understanding of how AI can be embedded into testing workflows, including test optimization, data generation, and impact analysis.

Mandatory Skills

• Strong proficiency in Core Java, including ability to write optimized, clean code 
• Expertise in Selenium and modern test automation frameworks (TestNG, JUnit, custom frameworks) and prompt engineering skills at intermediate level.
• Solid understanding of Agile methodology, Scrum, and SDLC processes.
• Excellent analytical skills, debugging abilities, and problem-solving mindset.
• Effectively Collaborate with cross functional teams to deliver high quality product delivery

 

Career Level - IC2

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